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BigData News Wednesday, March 28 Linear algebra, Deep learning, Funny cartoon & more…

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BigData News TLDR / Table of Contents

  • Deep Learning Book Series · Introduction
    • This content is part of a series following the chapter 2 on linear algebra from the Deep Learning Book by Goodfellow, I., Bengio, Y., and Courville, A. (…
    • linear algebra, deep learning, deep learning book, ,
  • The Browser of a Data Scientist
    • Yet another funny cartoon about data scientists. More cartoons about data science, can be found here.This one was originally posted here. As a bonus, here i…
    • funny cartoon, data science, Data Science Central, DSC Resources, data scientists
  • 10 Free Must-Read Books for Machine Learning and Data Science
    • algorithmic paradigms, data science ebooks, important algorithmic paradigms, bigger picture titles, fastest growing areas

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Deep Learning Book Series · Introduction

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  • This content is part of a series following the chapter 2 on linear algebra from the Deep Learning Book by Goodfellow, I., Bengio, Y., and Courville, A. (2016).
  • The aim of these notebooks is to help beginners/advanced beginners to grasp linear algebra concepts underlying deep learning and machine learning.
  • The goal of this series is to provide content for beginners who wants to understand enough linear algebra to be confortable with machine learning and deep learning.
  • However, I think that the chapter on linear algebra from the Deep Learning book is a bit tough for beginners.
  • Finally, we will see an example on how to solve a system of linear equations with the inverse matrix.

[/vc_column_text][vc_column_text el_class=”topfeed-tags”]Tags: linear algebra, deep learning, deep learning book, , [/vc_column_text][/vc_column][vc_column width=”1/2″][vc_separator][vc_column_text el_class=”topfeed-tweet”]

[/vc_column_text][vc_column_text el_class=”topfeed-embedly”]Deep Learning Book Series · Introduction[/vc_column_text][/vc_column][/vc_row][vc_row el_id=”The-Browser-of-a-Data-Scientist”][vc_column width=”1/2″][vc_separator][vc_column_text]

The Browser of a Data Scientist

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  • Yet another funny cartoon about data scientists.
  • More cartoons about data science, can be found here.

[/vc_column_text][vc_column_text el_class=”topfeed-tags”]Tags: funny cartoon, data science, Data Science Central, DSC Resources, data scientists[/vc_column_text][/vc_column][vc_column width=”1/2″][vc_separator][vc_column_text el_class=”topfeed-tweet”]

[/vc_column_text][vc_column_text el_class=”topfeed-embedly”]The Browser of a Data Scientist – Data Science Central[/vc_column_text][/vc_column][/vc_row][vc_row el_id=”10-Free-Must-Read-Books-for-Machine-Learning-and-Data-Science”][vc_column width=”1/2″][vc_separator][vc_column_text]

10 Free Must-Read Books for Machine Learning and Data Science

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  • With that in mind, here’s a list of 10 free machine learning and data science titles to get your spring reading started right.
  • What better way to enjoy this spring weather than with some free machine learning and data science ebooks?
  • The book provides a theoretical account of the fundamentals underlying machine learning and the mathematical derivations that transform these principles into practical algorithms.
  • The Elements of Statistical Learning – – By Trevor Hastie, Robert Tibshirani and Jerome Friedman – – This book descibes the important ideas in these areas in a common conceptual framework.
  • The textbook is laid out as a series of small steps that build on each other until, by the time you complete the book, you have laid the foundation for understanding data mining techniques.

[/vc_column_text][vc_column_text el_class=”topfeed-tags”]Tags: algorithmic paradigms, data science ebooks, important algorithmic paradigms, bigger picture titles, fastest growing areas[/vc_column_text][/vc_column][vc_column width=”1/2″][vc_separator][vc_column_text el_class=”topfeed-tweet”]

[/vc_column_text][vc_column_text el_class=”topfeed-embedly”]10 Free Must-Read Books for Machine Learning and Data Science[/vc_column_text][/vc_column][/vc_row]