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[PACKTPUB] MATHEMATICS FOR DATA SCIENCE AND MACHINE LEARNING USING R [VIDEO]

[PACKTPUB] MATHEMATICS FOR DATA SCIENCE AND MACHINE LEARNING USING R [VIDEO]

Eduonix Learning Solutions

September 27, 2019

11 hours 57 minutes

Learn the basic math for Data Science, AI, and ML using R

More Information

Learn
  • Master the basic math concepts you need for data science and Machine Learning
  • Learn to implement mathematical concepts using R
  • Master linear algebra, calculus, and vector calculus from the ground up
  • Master the R programming language
AboutWith data increasing every day, Data Science has become one of the most essential aspects in most fields. From healthcare to business, data is essential everywhere. However, it revolves around three major aspects: data itself, foundational concepts, and programming languages that interpret data.This course teaches you everything you need to know about the basic math for Data Science via the R programming language, developed specifically to perform statistics and data analytics and utilize graphical modules more effectively.

Data Science has become an interdisciplinary field that deals with the processes and systems used to extract knowledge or make predictions from large amounts of data. From helping brands to understand their customers to solve complex IT problems, its usability in almost every other field makes it very important for the functioning and growth of organizations or companies. We supply an overview of Machine Learning and the R programming language, linear algebra- scalars, vectors, matrices, linear regression, calculus-tangents, derivatives, vector calculus, vector spaces, Gradient Descent, and others.

All the codes and supporting files for this course are available at – https://github.com/PacktPublishing/Mathematics-for-Data-Science-and-Machine-Learning-using-R

Features
  • Understand linear algebra – scalars, vectors, and matrices
  • Understand the fundamental mathematics for data science, AI, and ML using R
Course Length11 hours 57 minutes
ISBN9781839210945
Date Of Publication27 Sep 2019

Size: 3.79G

 

 

 

 



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