Advanced Statistics and Data Mining for Data Science
What Will You Learn
■ Get acquainted with data mining techniques and advanced statistics
■ Become an expert in linear regression
■ Learn to distinguish between the several kinds of predictive models
■ Work with neural networks
■ Find out the decision tree results
■ Understand when to use association modeling and perform cluster analysis
Data Science is a field that is consistently evolving. Data Science includes theories and techniques extracted from computer science, statistics, and machine learning. This video course will ensure that you become an expert at various statistical techniques and data mining. The course begins with a contrast and comparison between data mining and statistics followed by providing an overview of the different kinds of projects usually encountered by data scientists. Next, you will learn classification/predictive modeling which is the most common kind of data analysis project. As you progress through your journey, three methods will be introduced to you: decision tree, statistical, and machine learning. You can perform these methods through predictive modeling. Finally, you will be able to learn the art of cluster analysis through exploring segmentation modeling. You will also work with association modeling at the end which will let you perform market basket analysis.
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StartPredictive Modeling Purpose, Examples, and Types (4:37)
StartCharacteristics and Examples of Statistical Predictive Models (2:12)
StartLinear Regression Purpose, Formulas, and Demonstration (10:00)
StartLinear Regression Assumptions (5:53)
StartCharacteristics and Examples of Decision Trees Models (2:27)
StartCHAID Purpose and Theory (2:49)
StartCHAID Demonstration (5:45)
StartCHAID Interpretation (9:38)
StartCharacteristics and Examples of Machine Learning Models (2:23)
StartNeural Network Purpose and Theory (4:29)
StartNeural Network Demonstration (7:29)
StartComparing Models (5:45)