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Data Mining: Mastering Data Mining Skills | Part - 1
 
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In this video, Qasim Ali Shah talking on the topic "DATA MINING SKILLS". In this session you will know about the content of trainers. He is giving some useful tips to all students, like: how should you can select your topic to speak effectively and after this what type of content will be helpful for your topic. You will know so many more after watching this video regarding above given topic. ===== ABOUT Qasim Ali Shah ===== Qasim Ali Shah is a Public Speaker- Teacher- Writer- Corporate Trainer & Leader for every age group- Businessmen- Corporate executives- Employees- Students- Housewives- Networkers- Sportsmen and for all who wish everlasting Success- Happiness- Peace and Personal Growth. He helps people to change their belief & thought pattern- experience less stress and more success in their lives through better communication- positive thinking and spiritual knowledge. ===== FOLLOW ME ON THE SOCIALS ===== - Qasim Ali Shah: https://goo.gl/6BKcxu - Google+: https://goo.gl/uPyGvT - Twitter: https://goo.gl/78MVoA - Website : https://goo.gl/Tgjy6u ===== Team Member: Waqas Nasir =====
Views: 9067 Qasim Ali Shah
What is Data Mining  -Mastering Data Mining Skills - ( Part 2 )
 
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About Qasim Ali Shah, Qasim Ali Shah is a Public Speaker- Teacher- Writer- Corporate Trainer & Leader for every age group- Businessmen- Corporate executives- Employees- Students- Housewives- Networkers- Sportsmen and for all who wish everlasting Success- Happiness- Peace and Personal Growth. He helps people to change their belief & thought pattern- experience less stress and more success in their lives through better communication- positive thinking and spiritual knowledge. Facebook Page. https://www.facebook.com/m.adil081 Twitter, https://twitter.com/madil081 Instagram, https://www.instagram.com/m.adil081/ Youtube, https://www.youtube.com/channel/UCCdzENcuIZq-2IDgokQw-yg Google+, https://plus.google.com/u/0/115997488022496813711 Tune.pk, https://tune.pk/user/QasimAliShahStudents Web, https://madil081.blogspot.com/ Web 2 https://madil081.tumblr.com/
Data Mining: Mastering Data Mining Skills | Part - 2
 
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In this video, Qasim Ali Shah talking on the topic "DATA MINING SKILLS". In this session you will know about the content of trainers. He is giving some useful tips to all students, like: how should you can select your topic to speak effectively and after this what type of content will be helpful for your topic. You will know so many more after watching this video regarding above given topic. ===== ABOUT Qasim Ali Shah ===== Qasim Ali Shah is a Public Speaker- Teacher- Writer- Corporate Trainer & Leader for every age group- Businessmen- Corporate executives- Employees- Students- Housewives- Networkers- Sportsmen and for all who wish everlasting Success- Happiness- Peace and Personal Growth. He helps people to change their belief & thought pattern- experience less stress and more success in their lives through better communication- positive thinking and spiritual knowledge. ===== FOLLOW ME ON THE SOCIALS ===== - Qasim Ali Shah: https://goo.gl/6BKcxu - Google+: https://goo.gl/uPyGvT - Twitter: https://goo.gl/78MVoA - Website : https://goo.gl/Tgjy6u ===== Team Member: Waqas Nasir =====
Views: 7999 Qasim Ali Shah
Data Mining  -Mastering Data Mining Skills - ( Part 1 ) By Qasim Ali Shah Students
 
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About Qasim Ali Shah, Qasim Ali Shah is a Public Speaker- Teacher- Writer- Corporate Trainer & Leader for every age group- Businessmen- Corporate executives- Employees- Students- Housewives- Networkers- Sportsmen and for all who wish everlasting Success- Happiness- Peace and Personal Growth. He helps people to change their belief & thought pattern- experience less stress and more success in their lives through better communication- positive thinking and spiritual knowledge. Facebook Page. https://www.facebook.com/m.adil081 Twitter, https://twitter.com/madil081 Instagram, https://www.instagram.com/m.adil081/ Youtube, https://www.youtube.com/channel/UCCdzENcuIZq-2IDgokQw-yg Google+, https://plus.google.com/u/0/115997488022496813711 Tune.pk, https://tune.pk/user/QasimAliShahStudents Web, https://madil081.blogspot.com/ Web 2 https://madil081.tumblr.com/
Mining Melancholy Restored to HD
 
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What you're hearing are the original samples used to create Mining Melancholy from Donkey Kong Country 2 Diddy's Kong Quest, combined with the music instruction data from the game, plus mixing and mastering magic for a perfect recreation of what a studio recording would have sounded like. All remasters currently progressed: https://www.dropbox.com/sh/g70cosiqz1tsjkp/AAAUWIfzy5jbc98_vVgXz2EWa/Restored%20Tracks?dl=0 Song composed by David Wise, restored by Jammin' Sam Miller & TerraBlue
Views: 68122 TerraBlue
ترجمة كتاب mastering python data analysis A : introduction
 
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ترجمة كتاب. Mastering python data analysis حمل الكتاب من هنا: http://file.allitebooks.com/20170122/Mastering%20Python%20Data%20Analysis.pdf ملفات الكتاب : https://github.com/PacktPublishing/Mastering-Python-Data-Analysis
Views: 349 superlinux
Mastering Data Mining
 
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Mastering Data Mining: The Art And Science Of Customer Relationship Management. By Michael J. A. Berry, Gordon S. Linof... http://www.thebookwoods.com/book02/0471331236.html Author of the book in this video: Michael J. A. Berry Gordon S. Linoff The book in this video is published by: Wiley THE MAKER OF THIS VIDEO IS NOT AFFILIATED WITH OR ENDORSED BY THE PUBLISHING COMPANIES OR AUTHORS OF THE BOOK IN THIS VIDEO. ---- DISCLAIMER --- Copyright Disclaimer Under Section 107 of the Copyright Act 1976, allowance is made for fair use for purposes such as criticism, comment, news reporting, teaching, scholarship, and research. Fair use is a use permitted by copyright statute that might otherwise be infringing. Non-profit, educational or personal use tips the balance in favor of fair use. All content in this video and written content are copyrighted to their respective owners. All book covers and art are copyrighted to their respective publishing companies and/or authors. We do not own, nor claim ownership of any images used in this video. All credit for the images or photography go to their rightful owners.
Views: 37 Johan Lidrag Hagen
Lecture 46 — Dimensionality Reduction - Introduction | Stanford University
 
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. Copyright Disclaimer Under Section 107 of the Copyright Act 1976, allowance is made for "FAIR USE" for purposes such as criticism, comment, news reporting, teaching, scholarship, and research. Fair use is a use permitted by copyright statute that might otherwise be infringing. Non-profit, educational or personal use tips the balance in favor of fair use. .
Introduction To Data Analytics With Pandas || Quentin Caudron
 
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Data analytics in Python benefits from the beautiful API offered by the pandas library. With it, manipulating and analysing data is fast and seamless. In this workshop, we'll take a hands-on approach to performing an exploratory analysis in pandas. We'll begin by importing some real data. Then, we'll clean it, transform it, and analyse it, finishing with some visualisations. EVENT: PyData Seattle 2017 SPEAKER: Quentin Caudron PERMISSIONS: PyData provided Coding Tech with the permission to republish this video. CREDITS: Original video source: https://www.youtube.com/watch?v=F7sCL61Zqss
Views: 4035 Coding Tech
Is Data Science A Viable Career Path?
 
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I am doing a bachelor of computer science and have not yet chosen a discipline to major in. My lecturer mentioned the disciplines and one grabbed my attention: Data Science. He explained how data science is the future of technology and gave some examples. Do you believe that data science is the future and can you please explain what it is in a little more detail? -Abraham A. Schedule a Skype Meeting with Eli: https://silicondiscourse.com Podcasts of New Videos at SoundCloud: https://soundcloud.com/elithecomputerguy To Ask Questions Email: [email protected] For Classes, Class Notes and Blog Posts: http://www.EliTheComputerGuy.com Visit the Main YouTube Channel at: http://www.YouTube.com/EliTheComputerGuy Follow us on Twitter at: http://www.Twitter.com/EliComputerGuy **********
Views: 145921 Geek Field Notes
BI - Using Big Data & Social Mining in Value Chain Planning to reduce operational costs
 
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BI - Using Big Data & Social Mining in Value Chain Planning to reduce operational costs - Salil Amonkar, Bodhtree
Views: 213 Libing Chen
Record Breaking Months for Dealerships Using AutoAlert | Data Mining | Equity Mining
 
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AutoAlert credited for 52 units delivered during this Ford dealership's record-breaking month. AutoAlert will sell more cars at your dealership. The automotive retail industry's first customer experience management platform CXM We make complex, SIMPLE. One place. One login. Enhanced search functionality. Easily access top lease and retail opportunities. Identify service customers coming in for the day. View all customers with current offers. c/o Andrew Morse
Views: 96 AutoAlert
Data analysis in Python with pandas
 
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Wes McKinney The tutorial will give a hands-on introduction to manipulating and analyzing large and small structured data sets in Python using the pandas library. While the focus will be on learning the nuts and bolts of the library's features, I als
Views: 290565 Next Day Video
Simple Web Scraping using R
 
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Simple example of using R to extract structured content from web pages. There are several options and libraries that can be considered. if your webpage has data in HTML tables you can use readHTMLTable however in this example the web pages doesnt use HTML tables so we use a straightforward XPath technique to extract page content. We will in the end turn content from web pages into a data frame in R
Views: 33988 Melvin L
Top 4 Skills for a Data Analyst
 
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https://upgrad.com/data-analytics/ Thanks to the digital revolution, analytics is sweeping across industries in a huge way. Mastering certain data analytics skills can enable you to chart a successful career in this lucrative and rapidly changing domain. Data analytics is changing the way we live - from that app you use to navigate to work every day or the cabs you hail through your phone, or the platforms you order food from, to the online shopping you find yourself doing on weekends. All of this activity generates massive amounts of data. This is where companies who have created these products come in. Analytics is changing the way we also do business. Deriving insights from large volumes of data to enable better decision-making and an even better customer experience has become the norm for competitive firms these days. Which is why being a data analyst in this world pays off well. Through this UpGrad Careers-In-Shorts Series, let us go through all you need to know about data analytics - the most promising career of tomorrow! The first one here is about the 4 core skills that will help you transition to the field of data analytics - a career of the future.
Views: 30075 Rohit Sharma
Prospecting  Data Mine Your Own Leads and Generate More Business
 
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Prospecting: Data Mine Your Own Leads and Generate More Business WHICH WOULD YOU CHOOSE?? A. Wait on point, outside, all day to try and catch an “up” in the hopes that you will sell a car. B. Work smarter, not harder, and have the leads walk in the door and ask for you by name. It’s true! Instead of waiting for something to happen, you can take control of your destiny and increase your sales simply by knowing more than the other salespeople in the dealership! Automotive trainer Jennifer Suzuki is here to help! She is going to show how to use your CRM and other vendor tools to your prospecting advantage. She will also explain how to effectively use your existing leads to increase vehicle sales. Attendees of this fast-paced 1 hour webinar will learn how to create your own lead lists and will also obtain effective process maps with actual call, voicemail, text and email examples. Jennifer will share real success stories and will also bring in a guest salesperson who has been using these techniques to consistently sell 20+ cars a month - all from data-mining! ARE YOU READY TO GET YOUR HEAD IN THE GAME?? If you want to learn more about Prospecting and how to Data Mine Your Own Leads and Generate More Business then this is the presentation you have been waiting for! Don’t miss it!! NEW BIO: PRESENTER: Jennifer Suzuki is the Founder and President of e-Dealer Solutions, Inc., an award-winning training company. Jennifer’s passion and expertise are evident throughout her career as she has become well known for conducting monthly training seminars for the NADA Dealer Academy, NADA Convention Speaker, OEM Training, 20 Groups and State Associations. Her training is focused on converting non-present buyer’s to showroom appointments while improving sales teams phone skills, voicemails, emails, videos, chats and daily operating processes. In today’s harsh economy, dealerships require a unique and modern approach to working with the educated buyer to sell them cars — and that’s where Jennifer Suzuki comes in. Her 20 years of experience encompasses a wide gamut of valuable auto industry know-how, such as: selling vehicles, training and installing DMS systems, retailing internet leads, and managing an internet sales division comprised of 28 dealerships. She has a tremendous reputation for delivering in-dealership and online training that significantly improves dealership sales. Jennifer Suzuki can be reached at 800.625.1590 and [email protected]
Views: 1005 Ali Amirrezvani
Mastering Data Visualization with R 01
 
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Mastering Data Visualization with R
Views: 11 林楚賢
Excel Data Analysis: Sort, Filter, PivotTable, Formulas (25 Examples): HCC Professional Day 2012
 
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Download workbook: http://people.highline.edu/mgirvin/ExcelIsFun.htm Learn the basics of Data Analysis at Highline Community College Professional Development Day 2012: Topics in Video: 1. What is Data Analysis? ( 00:53 min mark) 2. How Data Must Be Setup ( 02:53 min mark) Sort: 3. Sort with 1 criteria ( 04:35 min mark) 4. Sort with 2 criteria or more ( 06:27 min mark) 5. Sort by color ( 10:01 min mark) Filter: 6. Filter with 1 criteria ( 11:26 min mark) 7. Filter with 2 criteria or more ( 15:14 min mark) 8. Filter by color ( 16:28 min mark) 9. Filter Text, Numbers, Dates ( 16:50 min mark) 10. Filter by Partial Text ( 20:16 min mark) Pivot Tables: 11. What is a PivotTable? ( 21:05 min mark) 12. Easy 3 step method, Cross Tabulation ( 23:07 min mark) 13. Change the calculation ( 26:52 min mark) 14. More than one calculation ( 28:45 min mark) 15. Value Field Settings (32:36 min mark) 16. Grouping Numbers ( 33:24 min mark) 17. Filter in a Pivot Table ( 35:45 min mark) 18. Slicers ( 37:09 min mark) Charts: 19. Column Charts from Pivot Tables ( 38:37 min mark) Formulas: 20. SUMIFS ( 42:17 min mark) 21. Data Analysis Formula or PivotTables? ( 45:11 min mark) 22. COUNTIF ( 46:12 min mark) 23. Formula to Compare Two Lists: ISNA and MATCH functions ( 47:00 min mark) Getting Data Into Excel 24. Import from CSV file ( 51:21 min mark) 25. Import from Access ( 54:00 min mark) Highline Community College Professional Development Day 2012 Buy excelisfun products: https://teespring.com/stores/excelisfun-store
Views: 1481696 ExcelIsFun
Mastering Machine Learning with MATLAB : Feature Selection | packtpub.com
 
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This playlist/video has been uploaded for Marketing purposes and contains only selective videos. For the entire video course and code, visit [http://bit.ly/2E4TL6x]. Selection of features is necessary to create a functional model so as to achieve a reduction in cardinality, imposing a limit greater than the number of features that must be considered during its creation. Feature selection is based on finding a subset of the original variables, usually iteratively, thus detecting new combinations of variables and comparing prediction errors. • Learn the basics of stepwise regression • Explore stepwise regression in MATLAB For the latest Big Data and Business Intelligence video tutorials, please visit http://bit.ly/1HCjJik Find us on Facebook -- http://www.facebook.com/Packtvideo Follow us on Twitter - http://www.twitter.com/packtvideo
Views: 1656 Packt Video
Mastering Python - An Excellent tool for Web Scraping and Data Analysis | Edureka
 
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Watch Sample Class recording: http://www.edureka.co/python?utm_source=youtube&utm_medium=webinar&utm_campaign=python-14-11-14 Python is a premiere open-source language. Along with having powerful libraries enabling data manipulation and analysis, it is a flexible, easy-to-use, and easy-to-learn language. Watch this video which explains the topics below: 1) Understand Python 2) Web Scrapping example using Python 3) Pydoop: Python API for Hadoop 4) Word count example in Pydoop 5) Integrate Data Science with Python 6) Implement Zombie Invasion modelling using Python Edureka is a New Age e-learning platform that provides Instructor-Led Live, Online classes for learners who would prefer a hassle free and self paced learning environment, accessible from any part of the world. The topics related to Python have extensively been covered in our course ‘Python for Big Data Analytics’. For more information, please write back to us at [email protected] Call us at US: 1800 275 9730 (toll free) or India: +91-8880862004
Views: 3115 edureka!
Matlab Training | Disease Prediction using Data Mining | Anova + PCA Features | SVM
 
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Disease prediction using data mining system using ANOVA2 + PCA and SVM classifier. An automated algorithm for disease prediction using MATLAB online training. For any further help contact us at [email protected] visit us at http://www.researchinfinitesolutions.com/ Direct at :: +91-6239359461 Whatsapp at :: +91-6239359461
Views: 16210 Fly High with AI
Text Analytics with R | How to Scrap Website Data for Text Analytics | Web Scrapping in R
 
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In this text analytics with R tutorial, I have talked about how you can scrap website data in R for doing the text analytics. This can automate the process of web analytics so that you are able to see when the new info is coming, you just run the R code and your analytics will be ready. Web scrapping in R is done by using the rvest package. Text analytics with R,how to scrap website data in R,web scraping in R,R web scraping,learn web scraping in R,how to get website data in R,how to fetch web data in R,web scraping with R,web scraping in R tutorial,web scraping in R analytics,web scraping in r rvest,web scraping and r,web scraping regex,web scraping facebook in r,r web scraping rvest,web scraping in R,web scraper with r,web scraping in r pdf,web scraping avec and r,web scraping and r
Data Mining
 
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-- Created using PowToon -- Free sign up at http://www.powtoon.com/join -- Create animated videos and animated presentations for free. PowToon is a free tool that allows you to develop cool animated clips and animated presentations for your website, office meeting, sales pitch, nonprofit fundraiser, product launch, video resume, or anything else you could use an animated explainer video. PowToon's animation templates help you create animated presentations and animated explainer videos from scratch. Anyone can produce awesome animations quickly with PowToon, without the cost or hassle other professional animation services require.
Views: 24000 Kiki Zachary
Module 1: Data Analysis in Excel
 
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This video is part of the Analyzing and Visualizing Data with Excel course available on EdX. To sign up for the course, visit: http://aka.ms/edxexcelbi
Views: 386491 DAT206x
Business Data Analysis with Excel
 
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Lecture Starts at: 8:25 Business data presents a challenge for the data analyst. Business data is often aggregated, recorded over time, and tends to exhibit autocorrelation. Additionally, and most problematically, the amount of business data is usually quite limited. These characteristics lead to a situation where many of the tools in the analyst's tool belt (e.g., regression) aren't ideal for the task. Despite these challenges, proper analysis of business data represents a fundamental skill required of Business/Data Analysts, Product/Program Managers, and Data Scientists. At this meetup presenter Dave Langer will show how to get started analyzing business data in a robust way using Excel – no programming or statistics required! Dave will cover the following during the presentation: • The types of business data and why business data is a unique analytical challenge. • Requirements for robust business data analysis. • Using histograms, running records, and process behavior charts to analyze business data. • The rules of trend analysis. • How to properly compare business data across time, organizations, geographies, etc.Where you can learn more about the tools and techniques. *Excel spreadsheets can be found here: https://github.com/datasciencedojo/meetup/tree/master/business_data_analysis_with_excel **Find out more about David here: https://www.meetup.com/data-science-dojo/events/236198327/ -- Learn more about Data Science Dojo here: https://hubs.ly/H0f8xWx0 See what our past attendees are saying here: https://hubs.ly/H0f8xGd0 -- Like Us: https://www.facebook.com/datasciencedojo/ Follow Us: https://plus.google.com/+Datasciencedojo Connect with Us: https://www.linkedin.com/company/data-science-dojo Also find us on: Google +: https://plus.google.com/+Datasciencedojo Instagram: https://www.instagram.com/data_science_dojo/ Vimeo: https://vimeo.com/datasciencedojo
Views: 43254 Data Science Dojo
Business Analytics and Data Mining Championship 2017
 
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NMIMS | SAS Business Analytics and Data Mining Championship 2017 - Overview
R tutorial: What is text mining?
 
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Learn more about text mining: https://www.datacamp.com/courses/intro-to-text-mining-bag-of-words Hi, I'm Ted. I'm the instructor for this intro text mining course. Let's kick things off by defining text mining and quickly covering two text mining approaches. Academic text mining definitions are long, but I prefer a more practical approach. So text mining is simply the process of distilling actionable insights from text. Here we have a satellite image of San Diego overlaid with social media pictures and traffic information for the roads. It is simply too much information to help you navigate around town. This is like a bunch of text that you couldn’t possibly read and organize quickly, like a million tweets or the entire works of Shakespeare. You’re drinking from a firehose! So in this example if you need directions to get around San Diego, you need to reduce the information in the map. Text mining works in the same way. You can text mine a bunch of tweets or of all of Shakespeare to reduce the information just like this map. Reducing the information helps you navigate and draw out the important features. This is a text mining workflow. After defining your problem statement you transition from an unorganized state to an organized state, finally reaching an insight. In chapter 4, you'll use this in a case study comparing google and amazon. The text mining workflow can be broken up into 6 distinct components. Each step is important and helps to ensure you have a smooth transition from an unorganized state to an organized state. This helps you stay organized and increases your chances of a meaningful output. The first step involves problem definition. This lays the foundation for your text mining project. Next is defining the text you will use as your data. As with any analytical project it is important to understand the medium and data integrity because these can effect outcomes. Next you organize the text, maybe by author or chronologically. Step 4 is feature extraction. This can be calculating sentiment or in our case extracting word tokens into various matrices. Step 5 is to perform some analysis. This course will help show you some basic analytical methods that can be applied to text. Lastly, step 6 is the one in which you hopefully answer your problem questions, reach an insight or conclusion, or in the case of predictive modeling produce an output. Now let’s learn about two approaches to text mining. The first is semantic parsing based on word syntax. In semantic parsing you care about word type and order. This method creates a lot of features to study. For example a single word can be tagged as part of a sentence, then a noun and also a proper noun or named entity. So that single word has three features associated with it. This effect makes semantic parsing "feature rich". To do the tagging, semantic parsing follows a tree structure to continually break up the text. In contrast, the bag of words method doesn’t care about word type or order. Here, words are just attributes of the document. In this example we parse the sentence "Steph Curry missed a tough shot". In the semantic example you see how words are broken down from the sentence, to noun and verb phrases and ultimately into unique attributes. Bag of words treats each term as just a single token in the sentence no matter the type or order. For this introductory course, we’ll focus on bag of words, but will cover more advanced methods in later courses! Let’s get a quick taste of text mining!
Views: 21295 DataCamp
Mastering R Programming : Scraping Web Pages and Processing Texts | packtpub.com
 
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This playlist/video has been uploaded for Marketing purposes and contains only selective videos. For the entire video course and code, visit [http://bit.ly/2jDsrGS]. In this video, we'll take a look at how to scrape data from web pages and how to clean and process raw web and other textual data. • Show a web scraping example with rvest • Explain the structure of a typical webpage and basics of HTML and extract selector paths • Process and clean text data For the latest Big Data and Business Intelligence video tutorials, please visit http://bit.ly/1HCjJik Find us on Facebook -- http://www.facebook.com/Packtvideo Follow us on Twitter - http://www.twitter.com/packtvideo
Views: 3390 Packt Video
CSU-Global Master's of Science in Data Analytics
 
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www.csuglobal.edu/MSDA Earn Your Master’s Degree in Data Analytics Online Learn to be an organizational leader by mastering the many facets of business intelligence. Among the technical topics you’ll cover in the Master of Science in Data Analytics degree program are… Data warehousing. Data mining and visualization. Business Intelligence. Business analytics. Predictive analytics. Enterprise performance management.
Views: 1456 CSU-Global Campus
Google Analytics Data Mining with R (includes 3 Real Applications)
 
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R is already a Swiss army knife for data analysis largely due its 6000 libraries but until now it lacked an interface to the Google Analytics API. The release of RGoogleAnalytics library solves this problem. What this means is that digital analysts can now fully use the analytical capabilities of R to fully explore their Google Analytics Data. In this webinar, Andy Granowitz, ‎Developer Advocate (Google Analytics) & Kushan Shah, Contributor & maintainer of RGoogleAnalytics Library will show you how to use R for Google Analytics data mining & generate some great insights. Useful Resources:http://bit.ly/r-googleanalytics-resources
Views: 28198 Tatvic Analytics
Data Warehouse Interview Questions And Answers | Data Warehouse Tutorial | Edureka
 
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***** Data Warehousing & BI Training: https://www.edureka.co/data-warehousing-and-bi ***** This Data Warehouse Interview Questions And Answers tutorial will help you prepare for Data Warehouse interviews. Watch the entire video to get an idea of the 30 most frequently asked questions in Data Warehouse interviews. - - - - - - - - - - - - - - Check our complete Data Warehousing & Business Inelligence playlist here: https://goo.gl/DZEuZt. #DataWarehouseInterviewQuestions #DataWarehouseConcepts #DataWarehouseTutorial Subscribe to our channel to get video updates. Hit the subscribe button above. - - - - - - - - - - - - - - How it Works? 1. This is a 5 Week Instructor led Online Course, 25 hours of assignment and 10 hours of project work 2. We have a 24x7 One-on-One LIVE Technical Support to help you with any problems you might face or any clarifications you may require during the course. 3. At the end of the training you will have to undergo a 2-hour LIVE Practical Exam based on which we will provide you a Grade and a Verifiable Certificate! - - - - - - - - - - - - - - About the Course: Edureka's Data Warehousing and Business Intelligence Course, will introduce participants to create and work with leading ETL & BI tools like: 1. Talend 5.x to create, execute, monitor and schedule ETL processes. It will cover concepts around Data Replication, Migration and Integration Operations 2. Tableau 9.x for data visualization to see how easy and reliable data visualization can become for representation with dashboards 3. Data Modeling tool ERwin r9 to create a Data Warehouse or Data Mart - - - - - - - - - - - - - - Who should go for this course? The following professionals can go for this course: 1. Data warehousing enthusiasts 2. Analytics Managers 3. Data Modelers 4. ETL Developers and BI Developers - - - - - - - - - - - - - - Why learn Data Warehousing and Business Intelligence? All the successful companies have been investing large sums of money in business intelligence and data warehousing tools and technologies. Up-to-date, accurate and integrated information about their supply chain, products and customers are critical for their success. With the advent of Mobile, Social and Cloud platform, today's business intelligence tools have evolved and can be categorized into five areas, including databases, extraction transformation and load (ETL) tools, data quality tools, reporting tools and statistical analysis tools. This course will provide a strong foundation around Data Warehousing and Business Intelligence fundamentals and sophisticated tools like Talend, Tableau and ERwin. - - - - - - - - - - - - - - Please write back to us at [email protected] or call us at +91 90660 20866 for more information. Facebook: https://www.facebook.com/edurekaIN/ Twitter: https://twitter.com/edurekain LinkedIn: https://www.linkedin.com/company/edureka - - - - - - - - - - - - - - Customer Review: Kanishk says, "Underwent Mastering in DW-BI Course. The training material and trainer are up to the mark to get yourself acquainted to the new technology. Very helpful support service from Edureka."
Views: 73286 edureka!
Big data and mining panel - 2018 Progressive Mine Forum
 
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A panel of experts discusses applications for big data in mining. This was recorded at the 2018 Progressive Mine Forum in Toronto, presented by The Northern Miner and Canadian Mining Journal. Moderator: John Cumming, The Northern Miner editor-in-chief. Panellists (from left): Talia Dabby, PwC Canada director; Glenn Mullan, PDAC president; Humera Malik, Canvas Analytics CEO; Gordon Stothart, Iamgold executive vice-president and chief operating officer; and Shelby Yee, RockMass Technologies co-founder and CEO.
Views: 109 The Northern Miner
How Big Data Is Used In Amazon Recommendation Systems | Big Data Application & Example | Simplilearn
 
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This Big Data Video will help you understand how Amazon is using Big Data is ued in their recommendation syatems. You will understand the importance of Big Data using case study. Recommendation systems have impacted or even redefined our lives in many ways. One example of this impact is how our online shopping experience is being redefined. As we browse through products, the Recommendation system offer recommendations of products we might be interested in. Regardless of the perspectives, business or consumer, Recommendation systems have been immensely beneficial. And big data is the driving force behind Recommendation systems. Subscribe to Simplilearn channel for more Big Data and Hadoop Tutorials - https://www.youtube.com/user/Simplilearn?sub_confirmation=1 Check our Big Data Training Video Playlist: https://www.youtube.com/playlist?list=PLEiEAq2VkUUJqp1k-g5W1mo37urJQOdCZ Big Data and Analytics Articles - https://www.simplilearn.com/resources/big-data-and-analytics?utm_campaign=Amazon-BigData-S4RL6prqtGQ&utm_medium=Tutorials&utm_source=youtube To gain in-depth knowledge of Big Data and Hadoop, check our Big Data Hadoop and Spark Developer Certification Training Course: http://www.simplilearn.com/big-data-and-analytics/big-data-and-hadoop-training?utm_campaign=Amazon-BigData-S4RL6prqtGQ&utm_medium=Tutorials&utm_source=youtube #bigdata #bigdatatutorialforbeginners #bigdataanalytics #bigdatahadooptutorialforbeginners #bigdatacertification #HadoopTutorial - - - - - - - - - About Simplilearn's Big Data and Hadoop Certification Training Course: The Big Data Hadoop and Spark developer course have been designed to impart an in-depth knowledge of Big Data processing using Hadoop and Spark. The course is packed with real-life projects and case studies to be executed in the CloudLab. Mastering real-time data processing using Spark: You will learn to do functional programming in Spark, implement Spark applications, understand parallel processing in Spark, and use Spark RDD optimization techniques. You will also learn the various interactive algorithm in Spark and use Spark SQL for creating, transforming, and querying data form. As a part of the course, you will be required to execute real-life industry-based projects using CloudLab. The projects included are in the domains of Banking, Telecommunication, Social media, Insurance, and E-commerce. This Big Data course also prepares you for the Cloudera CCA175 certification. - - - - - - - - What are the course objectives of this Big Data and Hadoop Certification Training Course? This course will enable you to: 1. Understand the different components of Hadoop ecosystem such as Hadoop 2.7, Yarn, MapReduce, Pig, Hive, Impala, HBase, Sqoop, Flume, and Apache Spark 2. Understand Hadoop Distributed File System (HDFS) and YARN as well as their architecture, and learn how to work with them for storage and resource management 3. Understand MapReduce and its characteristics, and assimilate some advanced MapReduce concepts 4. Get an overview of Sqoop and Flume and describe how to ingest data using them 5. Create database and tables in Hive and Impala, understand HBase, and use Hive and Impala for partitioning 6. Understand different types of file formats, Avro Schema, using Arvo with Hive, and Sqoop and Schema evolution 7. Understand Flume, Flume architecture, sources, flume sinks, channels, and flume configurations 8. Understand HBase, its architecture, data storage, and working with HBase. You will also understand the difference between HBase and RDBMS 9. Gain a working knowledge of Pig and its components 10. Do functional programming in Spark 11. Understand resilient distribution datasets (RDD) in detail 12. Implement and build Spark applications 13. Gain an in-depth understanding of parallel processing in Spark and Spark RDD optimization techniques 14. Understand the common use-cases of Spark and the various interactive algorithms 15. Learn Spark SQL, creating, transforming, and querying Data frames - - - - - - - - - - - Who should take up this Big Data and Hadoop Certification Training Course? Big Data career opportunities are on the rise, and Hadoop is quickly becoming a must-know technology for the following professionals: 1. Software Developers and Architects 2. Analytics Professionals 3. Senior IT professionals 4. Testing and Mainframe professionals 5. Data Management Professionals 6. Business Intelligence Professionals 7. Project Managers 8. Aspiring Data Scientists - - - - - - - - For more updates on courses and tips follow us on: - Facebook : https://www.facebook.com/Simplilearn - Twitter: https://twitter.com/simplilearn - LinkedIn: https://www.linkedin.com/company/simplilearn - Website: https://www.simplilearn.com Get the android app: http://bit.ly/1WlVo4u Get the iOS app: http://apple.co/1HIO5J0
Views: 24721 Simplilearn
IOM 528 - Data Warehousing Business Intelligence, and Data Mining - Professor Arif Ansari
 
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Professor Arif Ansari This course helps to build Business Analytics skill set required by companies. At least sixty percent of the class time is spent on data mining which is especially useful to companies, because it allows you to understand customers to a level not possible before. This course is about how companies apply two new technologies, data warehousing (DW) and data mining (DM, including business intelligence, BI) to empower their employees, and build and manage a customer-centric business model. Besides learning the strategic role DW and DM plays in an enterprise, you will also get a close-up look at DW and DM by working on cases and gaining hands-on experience using software tools. Students taking this class will get an overview of the technologies of DW and BI/DM from a managerial perspective. Finance companies have started data mining, example: Capital One Credit Card Company. Real Estate companies are now using neural networks to evaluate the price of homes.
Mine Cart Madness Restored to HD
 
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What you're hearing are the original samples used to create Mine Cart Madness from Donkey Kong Country, combined with the music instruction data from the game, plus mixing and mastering magic for a perfect recreation of what a studio recording would have sounded like. All remasters currently progressed: https://www.dropbox.com/sh/g70cosiqz1tsjkp/AAAUWIfzy5jbc98_vVgXz2EWa/Restored%20Tracks?dl=0 Song composed by David Wise, restored by Jammin' Sam Miller
Views: 22025 TerraBlue
Data Warehouse Tutorial For Beginners | Data Warehouse Concepts | Data Warehousing | Edureka
 
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***** Data Warehousing & BI Training: https://www.edureka.co/data-warehousing-and-bi ***** This Data Warehouse Tutorial For Beginners will give you an introduction to data warehousing and business intelligence. You will be able to understand basic data warehouse concepts with examples. The following topics have been covered in this tutorial: 1. What Is The Need For BI? 2. What Is Data Warehousing? 3. Key Terminologies Related To DWH Architecture: a. OLTP Vs OLAP b. ETL c. Data Mart d. Metadata 4. DWH Architecture 5. Demo: Creating A DWH - - - - - - - - - - - - - - Check our complete Data Warehousing & Business Intelligence playlist here: https://goo.gl/DZEuZt. #DataWarehousing #DataWarehouseTutorial #DataWarehouseTraining Subscribe to our channel to get video updates. Hit the subscribe button above. - - - - - - - - - - - - - - How it Works? 1. This is a 5 Week Instructor led Online Course, 25 hours of assignment and 10 hours of project work 2. We have a 24x7 One-on-One LIVE Technical Support to help you with any problems you might face or any clarifications you may require during the course. 3. At the end of the training you will have to undergo a 2-hour LIVE Practical Exam based on which we will provide you a Grade and a Verifiable Certificate! - - - - - - - - - - - - - - About the Course: Edureka's Data Warehousing and Business Intelligence Course, will introduce participants to create and work with leading ETL & BI tools like: 1. Talend 5.x to create, execute, monitor and schedule ETL processes. It will cover concepts around Data Replication, Migration and Integration Operations 2. Tableau 9.x for data visualization to see how easy and reliable data visualization can become for representation with dashboards 3. Data Modeling tool ERwin r9 to create a Data Warehouse or Data Mart - - - - - - - - - - - - - - Who should go for this course? The following professionals can go for this course: 1. Data warehousing enthusiasts 2. Analytics Managers 3. Data Modelers 4. ETL Developers and BI Developers - - - - - - - - - - - - - - Why learn Data Warehousing and Business Intelligence? All the successful companies have been investing large sums of money in business intelligence and data warehousing tools and technologies. Up-to-date, accurate and integrated information about their supply chain, products and customers are critical for their success. With the advent of Mobile, Social and Cloud platform, today's business intelligence tools have evolved and can be categorized into five areas, including databases, extraction transformation and load (ETL) tools, data quality tools, reporting tools and statistical analysis tools. This course will provide a strong foundation around Data Warehousing and Business Intelligence fundamentals and sophisticated tools like Talend, Tableau and ERwin. - - - - - - - - - - - - - - Please write back to us at [email protected] or call us at +91 90660 20866 for more information. Facebook: https://www.facebook.com/edurekaIN/ Twitter: https://twitter.com/edurekain LinkedIn: https://www.linkedin.com/company/edureka - - - - - - - - - - - - - - Customer Review: Kanishk says, "Underwent Mastering in DW-BI Course. The training material and trainer are up to the mark to get yourself acquainted to the new technology. Very helpful support service from Edureka."
Views: 177755 edureka!
Data Science in 25 Minutes with GP Pulipaka (Ganapathi Pulipaka): Mastering TensorFlow Tutorial
 
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Ganapathi Pulipaka Chief Data Scientist for AI strategy, neural network architectures, application development of Machine learning, Deep Learning algorithms, experience in applying algorithms, integrating IoT platforms, Python, PyTorch, R, JavaScript, Go Lang, and TensorFlow, Big Data, IaaS, IoT, Data Science, Blockchain, Apache Hadoop, Apache Kafka, Apache Spark, Apache Storm, Apache Flink, SQL, NoSQL, Mathematics, Data Mining, Statistical Framework, SIEM with 6+ Years of AI Research and Development Experience in AWS, Azure, and GCP. Education: PostDoc– CS, PhD in Machine Learning, AI, Big Data Analytics, Engineering and CS, Colorado Technical University, Colorado Springs PhD, Business Administration in Data Analytics, Management Information Systems and Enterprise Resource Management, California University, Irvine Design, develop, and deploy machine learning and deep learning applications to solve the real-world problems in natural language processing, speech recognition, text to speech, chatbots, and speech to text analytics. Experience in data exploration, data preparation, applying supervised and unsupervised machine learning algorithms, machine learning model training, machine learning model evaluation, predictive analytics, bio-inspired algorithms, genetic algorithms, and natural language processing. I wrote around 400 research papers, published two books as a bestselling author on Amazon "The Future of Data Science and Parallel Computing," "Big Data Appliances for In-Memory Computing: A Real-World Research Guide for Corporations to Tame and Wrangle Their Data," and with a vast number of big data tool installations, SQL, NoSQL, practical machine learning project implementations, data analytics implementations, applied mathematics and statistics for publishing with the Universities as part of academic research programs. Currently, I’m working a video course “Mastering PyTorch for Advanced Data Scientist,” to build millions of data scientists around the world for AI practice. I implemented Many projects for Fortune 100 corporations Aerospace, manufacturing, IS-AFS (Apparel footwear solutions), IS-MEDIA (Media and Entertainment), ISUCCS (Customer care services), IS-AUTOMOTIVE (Automotive), IS-Utilities, retail, high-tech, life sciences, healthcare, chemical industry, banking, and service management. Public Keynote Speaker on Robotics and artificial intelligence held on May 21-22 at Los Angeles, CA. Published eBook in November 2017 for SAP Leonardo IoT “The Digital Evolution of Supply Chain Management with SAP Leonardo,” sponsored by SAP. Published eBook in December 2017 for Change HealthCare (McKesson’s HealthCare Corporation) on Machine Learning and Artificial Intelligence for Enterprise HealthCare and Health. Building recommendation systems and applying algorithms for anomaly detection in the financial industry. Deep reinforcement learning algorithms for robotics and IoT. Applying convolutional neural networks, recurrent neural networks, and long-term short memory with deep learning techniques to solve various conundrums. Developed number of machine learning and deep learning programs applying various algorithms and published articles with architecture and practical project implementations on GitHub, medium.com, data driven investor Experience with Python, TensorFlow, Caffe, Theano, Keras, Java, and R Programming languages implementing stacked auto encoders, backpropagation, perceptron, Restricted Boltzmann machines, and Deep Belief Networks. Experience in multiple IoT platforms. Twitter: https://twitter.com/gp_pulipaka Facebook: https://www.facebook.com/ganapathipulipaka LinkedIn: https://www.linkedin.com/in/dr-ganapathi-pulipaka-56417a2
Views: 106 GP Pulipaka
Natural Language Processing (NLP) Tutorial | Data Science Tutorial | Simplilearn
 
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Natural language processing (NLP) is a field of computer science, artificial intelligence and computational linguistics concerned with the interactions between computers and human (natural) languages, and, in particular, concerned with programming computers to fruitfully process large natural language corpora. Python for Data Science Certification Training Course: https://www.simplilearn.com/big-data-and-analytics/python-for-data-science-training?utm_campaign=Data-Science-NLP-6WpnxmmkYys&utm_medium=SC&utm_source=youtube The Data Science with Python course is designed to impart an in-depth knowledge of the various libraries and packages required to perform data analysis, data visualization, web scraping, machine learning, and natural language processing using Python. The course is packed with real-life projects, assignment, demos, and case studies to give a hands-on and practical experience to the participants. Mastering Python and using its packages: The course covers PROC SQL, SAS Macros, and various statistical procedures like PROC UNIVARIATE, PROC MEANS, PROC FREQ, and PROC CORP. You will learn how to use SAS for data exploration and data optimization. Mastering advanced analytics techniques: The course also covers advanced analytics techniques like clustering, decision tree, and regression. The course covers time series, it's modeling, and implementation using SAS. As a part of the course, you are provided with 4 real-life industry projects on customer segmentation, macro calls, attrition analysis, and retail analysis. Who should take this course? There is a booming demand for skilled data scientists across all industries that make this course suited for participants at all levels of experience. We recommend this Data Science training especially for the following professionals: 1. Analytics professionals who want to work with Python 2. Software professionals looking for a career switch in the field of analytics 3. IT professionals interested in pursuing a career in analytics 4. Graduates looking to build a career in Analytics and Data Science 5. Experienced professionals who would like to harness data science in their fields 6. Anyone with a genuine interest in the field of Data Science For more updates on courses and tips follow us on: - Facebook : https://www.facebook.com/Simplilearn - Twitter: https://twitter.com/simplilearn Get the android app: http://bit.ly/1WlVo4u Get the iOS app: http://apple.co/1HIO5J0
Views: 20023 Simplilearn
Data Mining Biomedical Literature in the Cloud
 
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A large number of biomedical research articles are published every day, accumulating rich information, such as genetic variants, genes, phenotypes, diseases, and treatments. Rapid yet accurate text mining on large-scale scientific literature can discover novel knowledge to better understand human diseases, and to improve the quality of disease diagnosis, prevention, and treatment. In this contribution, we designed and developed an efficient text mining framework called "SparkText" on a Big Data infrastructure, which is composed of Apache Spark data streaming and machine learning algorithms, combined with Apache Cassandra No-SQL database. The SparkText is designed for mining large-scale scientific articles published on multiple journals. Please visit http://ahmadpahlavantafti.com/researchprojects.html for any further information!
Views: 160 Ahmad P. Tafti
Mastering Data Analysis with R - Associate - Prep Course : The Course Overview | packtpub.com
 
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This playlist/video has been uploaded for Marketing purposes and contains only selective videos. For the entire video course and code, visit [http://bit.ly/2sGg7GH]. This video will give an overview of entire course For the latest Application development video tutorials, please visit http://bit.ly/1HCjJik Find us on Facebook -- http://www.facebook.com/Packtvideo Follow us on Twitter - http://www.twitter.com/packtvideo
Views: 30 Packt Video
Data Mining For Accounting Part 1
 
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Dr. Edward Balli discusses the use of data mining as insight for accounting. This is part 1 of 4 that were presented at the 2009 Salford Analytics and Data Mining Conference in San Diego. To view the complete series of conference videos, please visit http://www.salford-systems.com/video/conference.html.
Views: 812 Salford Systems
The Complete MATLAB Course: Beginner to Advanced!
 
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Get The Complete MATLAB Course Bundle for 1 on 1 help! https://josephdelgadillo.com/product/matlab-course-bundle/ Get the courses directly on Udemy! Go From Beginner to Pro with MATLAB! http://bit.ly/2v1e0lL Machine Learn Fundamentals with MATLAB! http://bit.ly/2v3sQs6 The Ultimate Guide for MATLAB App Development! http://bit.ly/2GOodDN MATLAB for Programming and Data Analysis! http://bit.ly/2IIwpWL Enroll in the FREE Teachable course! http://jtdigital.teachable.com/p/matlab Time Stamps 00:51 What is Matlab, how to download Matlab, and where to find help 07:52 Introduction to the Matlab basic syntax, command window, and working directory 18:35 Basic matrix arithmetic in Matlab including an overview of different operators 27:30 Learn the built in functions and constants and how to write your own functions 42:20 Solving linear equations using Matlab 53:33 For loops, while loops, and if statements 1:09:15 Exploring different types of data 1:20:27 Plotting data using the Fibonacci Sequence 1:30:45 Plots useful for data analysis 1:38:49 How to load and save data 1:46:46 Subplots, 3D plots, and labeling plots 1:55:35 Sound is a wave of air particles 2:05:33 Reversing a signal 2:12:57 The Fourier transform lets you view the frequency components of a signal 2:27:25 Fourier transform of a sine wave 2:35:14 Applying a low-pass filter to an audio stream 2:43:50 To store images in a computer you must sample the resolution 2:50:13 Basic image manipulation including how to flip images 2:57:29 Convolution allows you to blur an image 3:02:51 A Gaussian filter allows you reduce image noise and detail 3:08:55 Blur and edge detection using the Gaussian filter 3:16:39 Introduction to Matlab & probability 3:19:47 Measuring probability 3:26:53 Generating random values 3:35:40 Birthday paradox 3:43:25 Continuous variables 3:48:00 Mean and variance 3:55:24 Gaussian (normal) distribution 4:03:21 Test for normality 4:10:32 2 sample tests 4:16:28 Multivariate Gaussian
Views: 917469 Joseph Delgadillo
R Programming For Beginners | R Language Tutorial | R Tutorial For Beginners | Edureka
 
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( R Training : https://www.edureka.co/r-for-analytics ) This Edureka R Programming Tutorial For Beginners (R Tutorial Blog: https://goo.gl/mia382) will help you in understanding the fundamentals of R and will help you build a strong foundation in R. Below are the topics covered in this tutorial: 1. Variables 2. Data types 3. Operators 4. Conditional Statements 5. Loops 6. Strings 7. Functions Check out our R Playlist: https://goo.gl/huUh7Y Subscribe to our channel to get video updates. Hit the subscribe button above. #R #Rtutorial #Ronlinetraining #Rforbeginners #Rprogramming How it Works? 1. This is a 5 Week Instructor led Online Course, 30 hours of assignment and 20 hours of project work 2. We have a 24x7 One-on-One LIVE Technical Support to help you with any problems you might face or any clarifications you may require during the course. 3. At the end of the training you will be working on a real time project for which we will provide you a Grade and a Verifiable Certificate! - - - - - - - - - - - - - - - - - About the Course Edureka's Data Analytics with R training course is specially designed to provide the requisite knowledge and skills to become a successful analytics professional. It covers concepts of Data Manipulation, Exploratory Data Analysis, etc before moving over to advanced topics like the Ensemble of Decision trees, Collaborative filtering, etc. During our Data Analytics with R Certification training, our instructors will help you: 1. Understand concepts around Business Intelligence and Business Analytics 2. Explore Recommendation Systems with functions like Association Rule Mining , user-based collaborative filtering and Item-based collaborative filtering among others 3. Apply various supervised machine learning techniques 4. Perform Analysis of Variance (ANOVA) 5. Learn where to use algorithms - Decision Trees, Logistic Regression, Support Vector Machines, Ensemble Techniques etc 6. Use various packages in R to create fancy plots 7. Work on a real-life project, implementing supervised and unsupervised machine learning techniques to derive business insights - - - - - - - - - - - - - - - - - - - Who should go for this course? This course is meant for all those students and professionals who are interested in working in analytics industry and are keen to enhance their technical skills with exposure to cutting-edge practices. This is a great course for all those who are ambitious to become 'Data Analysts' in near future. This is a must learn course for professionals from Mathematics, Statistics or Economics background and interested in learning Business Analytics. - - - - - - - - - - - - - - - - Why learn Data Analytics with R? The Data Analytics with R training certifies you in mastering the most popular Analytics tool. "R" wins on Statistical Capability, Graphical capability, Cost, rich set of packages and is the most preferred tool for Data Scientists. Below is a blog that will help you understand the significance of R and Data Science: Mastering R Is The First Step For A Top-Class Data Science Career Having Data Science skills is a highly preferred learning path after the Data Analytics with R training. Check out the upgraded Data Science Course For more information, please write back to us at [email protected] Call us at US: 1844 230 6362(toll free) or India: +91-90660 20867 Facebook: https://www.facebook.com/edurekaIN/ Twitter: https://twitter.com/edurekain LinkedIn: https://www.linkedin.com/company/edureka
Views: 249724 edureka!
Ethereum Q&A: Gas and resource allocation
 
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How is “gas” used in Ethereum, Ethereum Classic, and other smart contract platforms? What does “Turing complete” mean? As a smart contract developer, how do I estimate how much the execution of my program will cost in gas? These questions are from MOOC 9.7 session, which took place on March 30th 2018. Andreas is a teaching fellow with the University of Nicosia. The first course in their Master of Science in Digital Currency degree, DFIN-511: Introduction to Digital Currencies, is offered for free as an open enrollment MOOC course to anyone interested in learning about the fundamental principles. If you want early-access to talks and a chance to participate in the monthly live Q&As with Andreas, become a patron: https://www.patreon.com/aantonop RELATED: The Lion and the Shark: Divergent Evolution in Cryptocurrency - https://youtu.be/d0x6CtD8iq4 Investing in Education instead of Speculation - https://youtu.be/6uXAbJQoZlE Ethereum, ICOs, and Rocket Science - https://youtu.be/OWI5-AVndgk Slush17 Panel: Farewell to Centralised Data - https://youtu.be/ul0aGzF-v5c Blockchain vs. Bullshit: Thoughts On The Future of Money - https://youtu.be/SMEOKDVXlUo Why I'm writing 'Mastering Ethereum' - https://youtu.be/So6WERp7vLY Smart contract platforms - https://youtu.be/XU8Bc5oxneE Impact of smart contracts on law and accounting - https://youtu.be/K-TRzuPwJCc Altcoins and specialisation - https://youtu.be/b_Yhr8h6xnA Ether, ICOs, and securities - https://youtu.be/guBNLSsnAiA Unstoppable code - https://youtu.be/AQx3E3F8Kz4 Airdrop coins and privacy implications - https://youtu.be/JHRnqJJ0rhc Initial coin offerings (ICOs) - https://youtu.be/Q5R8KuxV4A0 The token ICO explosion - https://youtu.be/vdaW8NtJXuQ ICOs and responsible investment - https://youtu.be/C8UdbvrWyvg ICOs and financial regulation - https://youtu.be/Plu_WX3Gs8E ICOs, disruption, and self-regulation - https://youtu.be/yfjgcI8xX3A Scams, gambling, and regulation - https://youtu.be/fTI88YrN1UE ICOs and pyramid schemes - https://youtu.be/8HYWWP1QU7Q Directed acyclic graphs (DAGs) and IOTA - https://youtu.be/lfgMnbb5JeM Scaling and "Satoshi's vision" - https://youtu.be/Ub2LoTcYV54 "Blockchain, not Bitcoin " - https://youtu.be/r2f0HlaRdgo Reflections on the last five years - https://youtu.be/NoCi64uaFT0 Andreas M. Antonopoulos is a technologist and serial entrepreneur who has become one of the most well-known and respected figures in bitcoin. Follow on Twitter: @aantonop https://twitter.com/aantonop Website: https://antonopoulos.com/ He is the author of two books: “Mastering Bitcoin,” published by O’Reilly Media and considered the best technical guide to bitcoin; “The Internet of Money,” a book about why bitcoin matters. THE INTERNET OF MONEY, v1: https://www.amazon.co.uk/Internet-Money-collection-Andreas-Antonopoulos/dp/1537000454/ref=asap_bc?ie=UTF8 [NEW] THE INTERNET OF MONEY, v2: https://www.amazon.com/Internet-Money-Andreas-M-Antonopoulos/dp/194791006X/ref=asap_bc?ie=UTF8 MASTERING BITCOIN: https://www.amazon.co.uk/Mastering-Bitcoin-Unlocking-Digital-Cryptocurrencies/dp/1449374042 [NEW] MASTERING BITCOIN, 2nd Edition: https://www.amazon.com/Mastering-Bitcoin-Programming-Open-Blockchain/dp/1491954388 Translations of MASTERING BITCOIN: https://bitcoinbook.info/translations-of-mastering-bitcoin/ Subscribe to the channel to learn more about Bitcoin & open blockchains! Music: "Unbounded" by Orfan (https://www.facebook.com/Orfan/) Outro Graphics: Phneep (http://www.phneep.com/) Outro Art: Rock Barcellos (http://www.rockincomics.com.br/)
Views: 6109 aantonop

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