Statistics for Data Science [Video]

Statistics for Data Science [Video]

James D. Miller
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Leverage the power of statistics for Data Analysis, Classification, Regression, Machine Learning, and Neural Networks
Video
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RRP $124.99
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Video Details

ISBN 139781789345339
Course Length2 hours and 23 minutes

Video Description

Do you wish to be a data scientist but don't know where to begin? Want to implement statistics for data science? Want to get acquainted with R programs? Want to learn about the logic involved in computing statistics? If so, then this is the course for you.

This course will take you through an entire statistics odyssey, from knowing very little to becoming comfortable with using various statistical methods with data science tasks. It starts off with simple statistics and then moves on to statistical methods that are used in data science algorithms. R programs for statistical computation are clearly explained along with the logic. You will come across various mathematical concepts, such as variance, standard deviation, probability, matrix calculations, and more. You will learn only what is required to implement statistics in data science tasks such as data cleaning, mining, and analysis. You will learn the statistical techniques required to perform tasks such as linear regression, regularization, model assessment, boosting, SVMs, and working with neural networks.

By the end of the course, you will be comfortable with performing various statistical computations for data science programmatically.

Style and Approach

Step by step comprehensive guide with real-world examples that will help you leverage the power of statistics

What You Will Learn

  • Analyze the transition from a data developer to a data scientist mindset 
  • Get acquainted with R programs and the logic used for statistical computations 
  • Understand mathematical concepts such as variance, standard deviation, probability, matrix calculations, and more
  • Learn to implement statistics in data science tasks such as data cleaning, mining, and analysis
  • Learn the statistical techniques required to perform tasks such as linear regression, regularization, model assessment, boosting, SVMs, and working with neural networks
  • Get comfortable with performing various statistical computations for data science programmatically

Authors

Video Details

ISBN 139781789345339
Course Length2 hours and 23 minutes
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