Home
Search results “Forecast data mining”
Time Series Data Mining Forecasting with Weka
 
04:31
I am sorry for my poor english. I hope it helps you. when i take the data mining course, i had searched it but i couldnt. So i decided to share this video with you.
Views: 25050 Web Educator
Sales Forecasting with Excel and the SQL Server 2012 Data Mining Add-in Tutorial
 
04:30
Use the Excel Data Mining add-in for SQL 2012 Analysis Services. See how simple it is to build a predictive model that forecasts sales or other values based on historical data.
Views: 12852 Edward Kench
Forecast the Price of Gold with Excel and SQL Server - Data Mining Tutorial
 
06:15
Learn about data mining with SQL Server 2012 Analysis Services and Excel 2013, using historical gold pricing data, to predict future prices. To follow this tutorial, you should have SSAS and the Data Mining Add-in for Excel.
Views: 6572 Edward Kench
Microsoft Data Mining Demo -- Forecasting
 
02:16
Microsoft Data Mining Demo -- Forecasting with SQL Server 2008 and Excel 2007
Views: 8220 MarkTabNet
Excel 2013 - Data Mining - Forecast What If Scenario
 
04:47
Apresentação de como usar a ferramenta de mineração de dados do Excel 2013 para previsão de Forecast. Para mais acesse: http://excelb2b.com/
Views: 367 ExcelB2B
Advanced Data Mining with Weka (1.4: Looking at forecasts)
 
09:40
Advanced Data Mining with Weka: online course from the University of Waikato Class 1 - Lesson 4: Looking at forecasts http://weka.waikato.ac.nz/ Slides (PDF): https://goo.gl/JyCK84 https://twitter.com/WekaMOOC http://wekamooc.blogspot.co.nz/ Department of Computer Science University of Waikato New Zealand http://cs.waikato.ac.nz/
Views: 5259 WekaMOOC
Two Effective Algorithms for Time Series Forecasting
 
14:20
In this talk, Danny Yuan explains intuitively fast Fourier transformation and recurrent neural network. He explores how the concepts play critical roles in time series forecasting. Learn what the tools are, the key concepts associated with them, and why they are useful in time series forecasting. Danny Yuan is a software engineer in Uber. He’s currently working on streaming systems for Uber’s marketplace platform. This video was recorded at QCon.ai 2018: https://bit.ly/2piRtLl For more awesome presentations on innovator and early adopter topics, check InfoQ’s selection of talks from conferences worldwide http://bit.ly/2tm9loz Join a community of over 250 K senior developers by signing up for InfoQ’s weekly Newsletter: https://bit.ly/2wwKVzu
Views: 42584 InfoQ
SSAS: Forecast Video Tutorial (Data Mining Table Analysis Tool)
 
04:47
In this tutorial we will learn how to use the Forecast Table Analysis Tool for Excel 2007. See the video transcript: http://msdn.microsoft.com/en-us/library/dd299423.aspx
Views: 18752 sqlserver
Predicting the Winning Team with Machine Learning
 
29:37
Can we predict the outcome of a football game given a dataset of past games? That's the question that we'll answer in this episode by using the scikit-learn machine learning library as our predictive tool. Code for this video: https://github.com/llSourcell/Predicting_Winning_Teams Please Subscribe! And like. And comment. More learning resources: https://arxiv.org/pdf/1511.05837.pdf https://doctorspin.me/digital-strategy/machine-learning/ https://dashee87.github.io/football/python/predicting-football-results-with-statistical-modelling/ http://data-informed.com/predict-winners-big-games-machine-learning/ https://github.com/ihaque/fantasy https://www.credera.com/blog/business-intelligence/using-machine-learning-predict-nfl-games/ Join us in the Wizards Slack channel: http://wizards.herokuapp.com/ And please support me on Patreon: https://www.patreon.com/user?u=3191693 Follow me: Twitter: https://twitter.com/sirajraval Facebook: https://www.facebook.com/sirajology Instagram: https://www.instagram.com/sirajraval/ Instagram: https://www.instagram.com/sirajraval/ Signup for my newsletter for exciting updates in the field of AI: https://goo.gl/FZzJ5w Hit the Join button above to sign up to become a member of my channel for access to exclusive content!
Views: 98785 Siraj Raval
Time Series In R | Time Series Forecasting | Time Series Analysis | Data Science Training | Edureka
 
34:00
( Data Science Training - https://www.edureka.co/data-science ) In this Edureka YouTube live session, we will show you how to use the Time Series Analysis in R to predict the future! Below are the topics we will cover in this live session: 1. Why Time Series Analysis? 2. What is Time Series Analysis? 3. When Not to use Time Series Analysis? 4. Components of Time Series Algorithm 5. Demo on Time Series For more information, Please write back to us at [email protected] or call us at IND: 9606058406 / US: 18338555775 (toll free). Instagram: https://www.instagram.com/edureka_learning/ Facebook: https://www.facebook.com/edurekaIN/ Twitter: https://twitter.com/edurekain LinkedIn: https://www.linkedin.com/company/edureka
Views: 83930 edureka!
TIME SERIES ANALYSIS THE BEST EXAMPLE
 
26:05
QUANTITATIVE METHODS TIME SERIES ANALYSIS
Views: 206220 Adhir Hurjunlal
Time Series Analysis in Python | Time Series Forecasting | Data Science with Python | Edureka
 
38:20
** Python Data Science Training : https://www.edureka.co/python ** This Edureka Video on Time Series Analysis n Python will give you all the information you need to do Time Series Analysis and Forecasting in Python. Below are the topics covered in this tutorial: 1. Why Time Series? 2. What is Time Series? 3. Components of Time Series 4. When not to use Time Series 5. What is Stationarity? 6. ARIMA Model 7. Demo: Forecast Future Subscribe to our channel to get video updates. Hit the subscribe button above. Machine Learning Tutorial Playlist: https://goo.gl/UxjTxm #timeseries #timeseriespython #machinelearningalgorithms - - - - - - - - - - - - - - - - - About the Course Edureka’s Course on Python helps you gain expertise in various machine learning algorithms such as regression, clustering, decision trees, random forest, Naïve Bayes and Q-Learning. Throughout the Python Certification Course, you’ll be solving real life case studies on Media, Healthcare, Social Media, Aviation, HR. During our Python Certification Training, our instructors will help you to: 1. Master the basic and advanced concepts of Python 2. Gain insight into the 'Roles' played by a Machine Learning Engineer 3. Automate data analysis using python 4. Gain expertise in machine learning using Python and build a Real Life Machine Learning application 5. Understand the supervised and unsupervised learning and concepts of Scikit-Learn 6. Explain Time Series and it’s related concepts 7. Perform Text Mining and Sentimental analysis 8. Gain expertise to handle business in future, living the present 9. Work on a Real Life Project on Big Data Analytics using Python and gain Hands on Project Experience - - - - - - - - - - - - - - - - - - - Why learn Python? Programmers love Python because of how fast and easy it is to use. Python cuts development time in half with its simple to read syntax and easy compilation feature. Debugging your programs is a breeze in Python with its built in debugger. Using Python makes Programmers more productive and their programs ultimately better. Python continues to be a favorite option for data scientists who use it for building and using Machine learning applications and other scientific computations. Python runs on Windows, Linux/Unix, Mac OS and has been ported to Java and .NET virtual machines. Python is free to use, even for the commercial products, because of its OSI-approved open source license. Python has evolved as the most preferred Language for Data Analytics and the increasing search trends on python also indicates that Python is the next "Big Thing" and a must for Professionals in the Data Analytics domain. For more information, Please write back to us at [email protected] or call us at IND: 9606058406 / US: 18338555775 (toll free). Instagram: https://www.instagram.com/edureka_learning/ Facebook: https://www.facebook.com/edurekaIN/ Twitter: https://twitter.com/edurekain LinkedIn: https://www.linkedin.com/company/edureka
Views: 74659 edureka!
How to create a useful forecast model using Data Mining
 
03:02
Watch our latest video and learn how to build a forecast model regarding the price of aluminium for six months.
Views: 23 EX METRIX
Big Data and Weather Predictions: Don't Get Caught in the Rain
 
02:26
As storms, hurricanes and floods are getting more extreme, meteorologists are leveraging big data to more accurately predict and pinpoint climate events. Directed by Roxy Hunt Tony Castle Written & Narrated by Colin Weatherby Illustration by Amanda Ligman Animation & Sound Design by: Matt Schultz Shawna Schultz
Views: 5278 Mashable Brand X
Data Mining Excel 2010 2013 Modelo Forecast
 
20:41
Data Mining Excel 2010 2013 Modelo Forecast
Views: 162 AddKw
Synergent: The Power of Data Mining
 
00:16
Synergent uses your data to meet your campaign goals and improve the financial lives of your members.
Views: 5233 SynergentCorp
Predicting Stock Prices - Learn Python for Data Science #4
 
07:39
In this video, we build an Apple Stock Prediction script in 40 lines of Python using the scikit-learn library and plot the graph using the matplotlib library. The challenge for this video is here: https://github.com/llSourcell/predicting_stock_prices Victor's winning recommender code: https://github.com/ciurana2016/recommender_system_py Kevin's runner-up code: https://github.com/Krewn/learner/blob/master/FieldPredictor.py#L62 I created a Slack channel for us, sign up here: https://wizards.herokuapp.com/ Stock prediction with Tensorflow: https://nicholastsmith.wordpress.com/2016/04/20/stock-market-prediction-using-multi-layer-perceptrons-with-tensorflow/ Another great stock prediction tutorial: http://eugenezhulenev.com/blog/2014/11/14/stock-price-prediction-with-big-data-and-machine-learning/ This guy made 500K doing ML stuff with stocks: http://jspauld.com/post/35126549635/how-i-made-500k-with-machine-learning-and-hft Please share this video, like, comment and subscribe! That's what keeps me going. and please support me on Patreon!: https://www.patreon.com/user?u=3191693 Check out this youtube channel for some more cool Python tutorials: https://www.youtube.com/watch?v=RZF17FfRIIo Follow me: Twitter: https://twitter.com/sirajraval Facebook: https://www.facebook.com/sirajology Instagram: https://www.instagram.com/sirajraval/ Instagram: https://www.instagram.com/sirajraval/ Signup for my newsletter for exciting updates in the field of AI: https://goo.gl/FZzJ5w Hit the Join button above to sign up to become a member of my channel for access to exclusive content!
Views: 573913 Siraj Raval
Time Series Forecasting Theory | AR, MA, ARMA, ARIMA | Data Science
 
53:14
In this video you will learn the theory of Time Series Forecasting. You will what is univariate time series analysis, AR, MA, ARMA & ARIMA modelling and how to use these models to do forecast. This will also help you learn ARCH, Garch, ECM Model & Panel data models. For training, consulting or help Contact : [email protected] For Study Packs : http://analyticuniversity.com/ Analytics University on Twitter : https://twitter.com/AnalyticsUniver Analytics University on Facebook : https://www.facebook.com/AnalyticsUniversity Logistic Regression in R: https://goo.gl/S7DkRy Logistic Regression in SAS: https://goo.gl/S7DkRy Logistic Regression Theory: https://goo.gl/PbGv1h Time Series Theory : https://goo.gl/54vaDk Time ARIMA Model in R : https://goo.gl/UcPNWx Survival Model : https://goo.gl/nz5kgu Data Science Career : https://goo.gl/Ca9z6r Machine Learning : https://goo.gl/giqqmx Data Science Case Study : https://goo.gl/KzY5Iu Big Data & Hadoop & Spark: https://goo.gl/ZTmHOA
Views: 392655 Analytics University
Getting Started with Orange 06: Making Predictions
 
03:46
Making predictions with classification tree and logistic regression. Train data set: http://tinyurl.com/fruits-and-vegetables-train Test data set: http://tinyurl.com/test-fruits-and-vegetables License: GNU GPL + CC Music by: http://www.bensound.com/ Website: http://orange.biolab.si/ Created by: Laboratory for Bioinformatics, Faculty of Computer and Information Science, University of Ljubljana
Views: 68481 Orange Data Mining
Mod-01 Lec-02 Data Mining, Data assimilation and prediction
 
01:04:56
Dynamic Data Assimilation: an introduction by Prof S. Lakshmivarahan,School of Computer Science,University of Oklahoma.For more details on NPTEL visit http://nptel.ac.in
Views: 1912 nptelhrd
Making Predictions with Data and Python : Predicting Credit Card Default | packtpub.com
 
23:01
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/2eZbdPP]. Demonstrate how to build, evaluate and compare different classification models for predicting credit card default and use the best model to make predictions. • Introduce, load and prepare data for modeling • Show how to build different classification models • Show how to evaluate models and use the best to make predictions 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: 28740 Packt Video
Data Mining for Sales Forecasting using MS Excel a Video by Srikanth Seelam
 
01:16
As part of my research paper titled " Sales Forecasting using Data Mining: A case study on Wal-Mart". The video shows how to use the Data mining tools in excel and discuss the results obtained from Microsoft Time Series algorithm to predict the sales of Wal-Mart.
Views: 807 Srikanth Seelam
Forecasting - Linear regression - Example 1 - Part 1
 
24:05
In this video, you will learn how to find the demand forecast using linear regression.
Views: 72620 maxus knowledge
SSAS: Prediction Calculator - Data Mining Add-In
 
07:12
In this tutorial we will learn how to use the Prediction Calculator Table Analysis Tool for Excel 2007. Go to http://msdn.microsoft.com/en-us/library/dd299414.aspx for the full transcript
Views: 4828 sqlserver
Forecasting Time Series Data in R | Facebook's Prophet Package 2017 & Tom Brady's Wikipedia data
 
11:51
An example of using Facebook's recently released open source package prophet including, - data scraped from Tom Brady's Wikipedia page - getting Wikipedia trend data - time series plot - handling missing data and log transform - forecasting with Facebook's prophet - prediction - plot of actual versus forecast data - breaking and plotting forecast into trend, weekly seasonality & yearly seasonality components prophet procedure is an additive regression model with following components: - a piecewise linear or logistic growth curve trend - a yearly seasonal component modeled using Fourier series - a weekly seasonal component forecasting is an important tool related to analyzing big data or working in data science field. R is a free software environment for statistical computing and graphics, and is widely used by both academia and industry. R software works on both Windows and Mac-OS. It was ranked no. 1 in a KDnuggets poll on top languages for analytics, data mining, and data science. RStudio is a user friendly environment for R that has become popular.
Views: 22454 Bharatendra Rai
Stock Market Prediction
 
07:03
Can we predict the price of Microsoft stock using Machine Learning? We'll train the Random Forest, Linear Regression, and Perceptron models on many years of historical price data as well as sentiment from news headlines to find out! Code for this video: https://github.com/llSourcell/Stock_Market_Prediction Please Subscribe! And like. And comment. That's what keeps me going. Follow me: Twitter: https://twitter.com/sirajraval Facebook: https://www.facebook.com/sirajology More learning resources: https://www.quantinsti.com/blog/machine-learning-trading-predict-stock-prices-regression/ https://medium.com/@TalPerry/deep-learning-the-stock-market-df853d139e02 https://iknowfirst.com/rsar-machine-learning-trading-stock-market-and-chaos https://www.udacity.com/course/machine-learning-for-trading--ud501 https://quant.stackexchange.com/questions/111/how-can-i-go-about-applying-machine-learning-algorithms-to-stock-markets https://quant.stackexchange.com/questions/111/how-can-i-go-about-applying-machine-learning-algorithms-to-stock-markets http://eugenezhulenev.com/blog/2014/11/14/stock-price-prediction-with-big-data-and-machine-learning/ https://cloud.google.com/solutions/machine-learning-with-financial-time-series-data https://www.linkedin.com/pulse/deep-learning-stock-price-prediction-explained-joe-ellsworth If you're wondering why my voice sounds weird, it's because i was down with Traveler's Diarrhea from my recent trip to India. It's such a debilitating sickness, but the show must go on. And yes, thankfully I'm better now :) Join us in the Wizards Slack channel: http://wizards.herokuapp.com/ And please support me on Patreon: https://www.patreon.com/user?u=3191693 Follow me: Twitter: https://twitter.com/sirajraval Facebook: https://www.facebook.com/sirajology Instagram: https://www.instagram.com/sirajraval/ Instagram: https://www.instagram.com/sirajraval/ Signup for my newsletter for exciting updates in the field of AI: https://goo.gl/FZzJ5w Hit the Join button above to sign up to become a member of my channel for access to exclusive content!
Views: 81626 Siraj Raval
Predicting Football Matches Using Data With Jordan Tigani - Strata Europe 2014
 
13:56
A keynote address from Strata + Hadoop World Europe 2014 in Barcelona, "Predictive Analytics in the Cloud: Predicting Football." Watch more from Strata Europe 2014: http://goo.gl/uqw6WS Visit the Strata website to learn more: http://strataconf.com/strataeu2014/ Subscribe for more from the conference! http://goo.gl/szEauh How can you turn raw data into predictions? How can you take advantage of both cloud scalability and state-of-the-art Open Source Software? This talk shows how we built a model that correctly predicted the outcome of 14 of 16 games in the World Cup using Google’s Cloud Platform and tools like iPython and StatsModels. I’ll also demonstrate new tools to integrate iPython with Google’s cloud and how you can use the same tools to make your own predictions. About Jordan Tigani (Google): Jordan Tigani has more than 15 years of professional software development experience, the last 4 of which have been spent building BigQuery. Prior to joining Google, Jordan worked at a number of star-crossed startups, where he learned to make data-based predictions. He is a co-author of Google BigQuery Analytics. When not analyzing soccer matches, he can often be found playing in one. Stay Connected to O'Reilly Media by Email - http://goo.gl/YZSWbO Follow O'Reilly Media: http://plus.google.com/+oreillymedia https://www.facebook.com/OReilly https://twitter.com/OReillyMedia
Views: 92971 O'Reilly
AI for Marketing & Growth #1 - Predictive Analytics in Marketing
 
03:17
AI for Marketing & Growth #1 - Predictive Analytics in Marketing Download our list of the world's best AI Newsletters 👉https://hubs.ly/H0dL7N60 Welcome to our brand new AI for Marketing & Growth series in which we’ll get you up to speed on Predictive Analytics in Marketing! This series you-must-watch-this-every-two-weeks sort of series or you’re gonna get left behind.. Predictive analytics in marketing is a form of data mining that uses machine learning and statistical modeling to predict the future. Based on historical data. Applications in action are all around us already. For example, If your bank notifies you of suspicious activity on your bank card, it is likely that a statistical model was used to predict your future behavior based on your past transactions. Serious deviations from this pattern are flagged as suspicious. And that’s when you get the notification. So why should marketers care? Marketers can use it to help optimise conversions for their funnels by forecasting the best way to move leads down the different stages, turning them into qualified prospects and eventually converting them into paying customers. Now, if you can predict your customers’ behavior along the funnel, you can also think of messages to best influence that behavior and reach your customer’s highest potential value. This is super-intelligence for marketers! Imagine if you could not only determine whether a lead is a good fit for your product but also which are most promising. This’ll allow you to focus your team’s efforts on leads with the highest ROI. Which will also imply a shift in mindset. Going from quantity metrics, or how many leads you can attract, to quality metrics, or how many good leads you can engage. You can now easily predict your OMTM or KPIs in real-time and finally push vanity metrics aside. For example, based on my location, age, past purchases, and gender, how likely are you to buy eggs I if you just added milk to your basket? A supermarket can use this information to automatically recommend products to you A financial services provider can use thousands of data points created by your online behaviour to decide which credit card to offer you, and when. A fashion retailer can use your data to decide which shoes to recommend as your next purchase, based on the jacket you just bought. Sure, businesses can improve their conversion rates, but the implications are much bigger than that. Predictive analytics allows companies to set pricing strategies based on consumer expectations and competitor benchmarks. Retailers can predict demand, and therefore make sure they have the right level of stock for each of their products. The evidence of this revolution is already around us. Every time we type a search query into Google, Facebook or Amazon we’re feeding data into the machine. The machine thrives on data, growing ever more intelligent. To leverage the potential of artificial intelligence and predictive analytics, there are four elements that organizations need to put into place. 1. The right questions 2. The right data 3. The right technology 4. The right people Ok.. let’s look at some use cases of businesses that are already leveraging predictive analytics. Other topics discussed: Ai analytics case study artificial intelligence big data deep learning demand forecasting forecasting sales machine learning predictive analytics in marketing data mining statistical modelling predict the future historical data AI Marketing machine learning marketing machine learning in marketing artificial intelligence in marketing artificial intelligence AI Machine learning ------------------------------------------------------- Amsterdam bound? Want to make AI your secret weapon? Join our A.I. for Marketing and growth Course! A 2-day course in Amsterdam. No previous skills or coding required! https://hubs.ly/H0dkN4W0 OR Check out our 2-day intensive, no-bullshit, skills and knowledge Growth Hacking Crash Course: https://hubs.ly/H0dkN4W0 OR our 6-Week Growth Hacking Evening Course: https://hubs.ly/H0dkN4W0 OR Our In-House Training Programs: https://hubs.ly/H0dkN4W0 OR The world’s only Growth & A.I. Traineeship https://hubs.ly/H0dkN4W0 Make sure to check out our website to learn more about us and for more goodies: https://hubs.ly/H0dkN4W0 London Bound? Join our 2-day intensive, no-bullshit, skills and knowledge Growth Marketing Course: https://hubs.ly/H0dkN4W0 ALSO! Connect with Growth Tribe on social media and stay tuned for nuggets of wisdom, updates and more: Facebook: https://www.facebook.com/GrowthTribeIO/ LinkedIn: https://www.linkedin.com/company/growth-tribe Twitter: https://twitter.com/GrowthTribe/ Instagram: https://www.instagram.com/growthtribe/ Snapchat: growthtribe Video URL: https://youtu.be/uk82DHcU7z8
Views: 19876 Growth Tribe
Data Mining in the Cloud Installation et prevision
 
03:37
Video exemple du blog l'Echo Pilote : http://blogs.technet.com/echopilote illustrant comment installer l'add-in Microsoft Datamining in the cloud pour MS Excel. Une fois l'installation effectuée, un exemple de prévision (forecast) est réalisé. Cet add-in permet d'effectuer directement depuis Excel 2007 sans même avoir à installer SQL Server 2008 - différentes opérations d'analyse prédictives : forecast, segmentation, analyse de panier ... Il s'agit d'une version Beta. En revanche, un add-in complet est disponible dès lors que vous avez sql server 2008, vous pouvez le télécharger sur http://www.sqlserverdatamining.com
Views: 3007 frsql
Forecasting: Moving Averages, MAD, MSE, MAPE
 
04:52
This video shows how to calculate Moving Averages, and forecast error measures: The Mean Absolute Deviation or Error (MAD or MAE) The Mean Squared Error (MSE) and the Mean Absolute Percent Error (MAPE)
Views: 268500 Joshua Emmanuel
Video Tutorial - Creating Predictive Metrics for Forecasting in MicroStrategy Developer
 
25:41
In this brief video tutorial, Luiz Walther from our Customer Education team demonstrates how to create a predictive model in MicroStrategy Developer to create Forcasting Predictive Metrics.
MicroStrategy - Data Mining & Predictive Analytics - Online Training Video by MicroRooster
 
21:27
Source: MicroRooster.blogspot.com Format: A MicroStrategy Online Training Video blog. Description: An introduction to Data Mining & Predictive Analytics using MicroStrategy. This demo explains how to use MicroStrategy for performing advanced data science analysis. Must have some understanding of basic data mining to take advantage of this entry level demo.
Views: 17108 MicroRooster
Introduction to Data Mining in SQL Server Analysis Services
 
01:27:07
Data mining is one of the key hidden gems inside of Analysis Services but has traditionally had a steep learning curve. In this session, you'll learn how to create a data mining model to predict who is the best customer for you and learn how to use other algorithms to spend your marketing model wisely. You'll also see how to use Time Series analysis for budget and forecast prediction. Finally, you'll learn how to integrate data mining into your application through SSIS or custom coding.
Views: 11443 PASStv
Analytical Reporting Dashboard for Weather Data Mining Whitepaper- Part 1
 
01:02
Analytical Reporting Dashboard for Weather Data Mining Whitepaper Part 1- Summarizing the Data for Ready Analysis Finding and using reliable weather forecasts is becoming a key competitive advantage in many industries. To add to the complexity, the sheer number of forecasting services and their variability in the accuracy of their forecasts by geography, forecast timeframe and weather parameter makes it hard for many companies to choose the correct forecast. Decision-makers need an easy-to-use, actionable summary of the massive weather forecast and observation data This paper • This paper is part 1 of a two part series on building and using an analytical framework for determining forecast accuracy. • It focuses on issues related to getting the data ready for analysis in an analysis reporting tool such as Tableau • How MineWeather solves these problems and makes it easy for the users to summarize the data.
Views: 159 Macrosoft Inc
Predictive Modelling Techniques | Data Science With R Tutorial
 
03:10:36
This lesson will teach you Predictive analytics and Predictive Modelling Techniques. Watch the New Upgraded Video: https://www.youtube.com/watch?v=DtOYBxi4AIE After completing this lesson you will be able to: 1. Understand regression analysis and types of regression models 2. Know and Build a simple linear regression model 3. Understand and develop a logical regression 4. Learn cluster analysis, types and methods to form clusters 5. Know more series and its components 6. Decompose seasonal time series 7. Understand different exponential smoothing methods 8. Know the advantages and disadvantages of exponential smoothing 9. Understand the concepts of white noise and correlogram 10. Apply different time series analysis like Box Jenkins, AR, MA, ARMA etc 11. Understand all the analysis techniques with case studies Regression Analysis: • Regression analysis mainly focuses on finding a relationship between a dependent variable and one or more independent variables. • It predicts the value of a dependent variable based on one or more independent variables • Coefficient explains the impact of changes in an independent variable on the dependent variable. • Widely used in prediction and forecasting Data Science with R Language Certification Training: https://www.simplilearn.com/big-data-and-analytics/data-scientist-certification-r-tools-training?utm_campaign=Predictive-Analytics-0gf5iLTbiQM&utm_medium=SC&utm_source=youtube #datascience #datasciencetutorial #datascienceforbeginners #datasciencewithr #datasciencetutorialforbeginners #datasciencecourse The Data Science with R training course has been designed to impart an in-depth knowledge of the various data analytics techniques which can be performed using R. The course is packed with real-life projects, case studies, and includes R CloudLabs for practice. Mastering R language: The course provides an in-depth understanding of the R language, R-studio, and R packages. You will learn the various types of apply functions including DPYR, gain an understanding of data structure in R, and perform data visualizations using the various graphics available in R. Mastering advanced statistical concepts: The course also includes the various statistical concepts like linear and logistic regression, cluster analysis, and forecasting. You will also learn hypothesis testing. As a part of the course, you will be required to execute real-life projects using CloudLab. The compulsory projects are spread over four case studies in the domains of healthcare, retail, and Internet. R CloudLab has been provided to ensure a practical and hands-on experience. Additionally, we have four more projects for further practice. Who should take this course? There is an increasing demand for skilled data scientists across all industries which makes this course suited for participants at all levels of experience. We recommend this Data Science training especially for the following professionals: 1. IT professionals looking for a career switch into data science and analytics 2. Software developers looking for a career switch into data science and analytics 3. Professionals working in data and business analytics 4. Graduates looking to build a career in analytics and data science 5. Anyone with a genuine interest in the data science field 6. Experienced professionals who would like to harness data science in their fields 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: 214276 Simplilearn
Excel 2016 Planilha de Previsão (Forecast)
 
05:18
Novo recurso do Excel 2016 que permite análise preditiva com base em dados históricos. Antes disponível apenas no complemento de data mining, agora está bem mais fácil de usar diretamente como recurso nativo.
Views: 3847 Leandro Barbieri
Data Mining Lecture -- Decision Tree | Solved Example (Eng-Hindi)
 
29:13
-~-~~-~~~-~~-~- Please watch: "PL vs FOL | Artificial Intelligence | (Eng-Hindi) | #3" https://www.youtube.com/watch?v=GS3HKR6CV8E -~-~~-~~~-~~-~-
Views: 194295 Well Academy
Analytical Reporting Dashboard for Weather Data Mining- Part 2
 
01:07
Mine-Weather reporting framework allows end users to compare different weather forecast services by parameter scores. This is a metric calculated using statistical principles by comparing forecasts and actual observational weather parameters (TEMPERATURE, WIND SPEED, RAINFALL RATE, ETC.)
Views: 75 Macrosoft Inc
Data Mining Tools Market Size, Status and Forecast 2018 2025
 
00:43
Visit Here : http://bit.ly/2z2jXOh Data Mining Tools market size was million US$ and it is expected to reach million US$ by the end of 2025, with a CAGR of during 2018-2025. This report focuses on the global Data Mining Tools status, future forecast, growth opportunity, key market and key players. The study objectives are to present the Data Mining Tools development in United States, Europe and China.
Import data from web to excel - Sports | Statistics | Weather forecast
 
10:31
Import data into dynamic tables in Excel and stay up to date with latest information without browsing, Run time data or statistics analysis, maybe it be Sports information, weather forecast or statistics,connect link once and enjoy forever, illustrated with multiple examples.
Views: 20998 Excel to Excel
FORECAST - EXCEL MINERIA DE DATOS
 
07:20
DATA MINING EN EXCEL UTILIZANDO LA HERRAMIENTA FORECAST, EJEMPLO Y SU FUNCIONAMIENTO
Views: 19044 Lucita287
Linear Regression - Machine Learning Fun and Easy
 
07:47
Linear Regression - Machine Learning Fun and Easy ►FREE YOLO GIFT - http://augmentedstartups.info/yolofreegiftsp ►KERAS Course - https://www.udemy.com/machine-learning-fun-and-easy-using-python-and-keras/?couponCode=YOUTUBE_ML ►MACHIN LEARNING COURSE - http://augmentedstartups.info/machine-learning-courses ---------------------------------------------------------------------------- Hi and welcome to a new lecture in the Fun and Easy Machine Learning Series. Today I’ll be talking about Linear Regression. We show you also how implement a linear regression in excel Linear regression attempts to model the relationship between two variables by fitting a linear equation to observed data. One variable is considered to be an explanatory variable, and the other is considered to be a dependent variable. Dependent Variable – Variable who’s values we want to explain or forecast Independent or explanatory Variable that Explains the other variable. Values are independent. Dependent variable can be denoted as y, so imagine a child always asking y is he dependent on his parents. And then you can imagine the X as your ex boyfriend/girlfriend who is independent because they don’t need or depend on you. A good way to remember it. Anyways Used for 2 Applications To Establish if there is a relation between 2 variables or see if there is statistically signification relationship between the two variables- • To see how increase in sin tax has an effect on how many cigarettes packs are consumed • Sleep hours vs test scores • Experience vs Salary • Pokemon vs Urban Density • House floor area vs House price Forecast new observations – Can use what we know to forecast unobserved values Here are some other examples of ways that linear regression can be applied. • So say the sales of ROI of Fidget spinners over time. • Stock price over time • Predict price of Bitcoin over time. Linear Regression is also known as the line of best fit The line of best fit can be represented by the linear equation y = a + bx or y = mx + b or y = b0+b1x You most likely learnt this in school. So b is is the intercept, if you increase this variable, your intercept moves up or down along the y axis. M is your slope or gradient, if you change this, then your line rotates along the intercept. Data is actually a series of x and y observations as shown on this scatter plot. They do not follow a straight line however they do follow a linear pattern hence the term linear regression Assuming we already have the best fit line, We can calculate the error term Epsilon. Also known as the Residual. And this is the term that we would like to minimize along all the points in the data series. So say if we have our linear equation but also represented in statisitical notation. The residual fit in to our equation as shown y = b0+b1x + e ------------------------------------------------------------ Support us on Patreon ►AugmentedStartups.info/Patreon Chat to us on Discord ►AugmentedStartups.info/discord Interact with us on Facebook ►AugmentedStartups.info/Facebook Check my latest work on Instagram ►AugmentedStartups.info/instagram Learn Advanced Tutorials on Udemy ►AugmentedStartups.info/udemy ------------------------------------------------------------ To learn more on Artificial Intelligence, Augmented Reality IoT, Deep Learning FPGAs, Arduinos, PCB Design and Image Processing then check out http://augmentedstartups.info/home Please Like and Subscribe for more videos :)
Views: 143660 Augmented Startups
Current mining production data and 2011 forecast with Peter Major
 
10:49
(www.abndigital.com) Last year the Resource 20 sector was one of the worst performing with a return of only 12.28 percent. Joining me on the desk to discuss mining production as well as what we can expect from this sector in 2011 is Peter Major, Fund Manager at Cadiz Corporate Solutions.
Views: 56 CNBCAfrica
R-Programming | Analyzing House Prices in King County, USA
 
11:06
A data analysis project that I worked on for my final project in my R-Programming course. I incorporate the use of three very popular R-Packages in "ggplot2", "ggmap", and "dplyr". I also create a multiple linear regression to showcase what variables most heavily affect house price. I then map some of the most expensive homes in this county on a hybrid map using the ggmap package. Link to Data Set: http://bit.ly/2qEQkOa
Views: 2640 EadsGraphic
Big Data: Mining Football Statistics
 
08:45
Data Mining Final Project for Big Data INSY 4970 at Auburn University
Views: 34195 wwl0002

Rock boy britney spears download video
Downtown music in little rock arkansas
World music link corporation
Classical music for sleep online radio
Kids holiday music radio