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Best Data Science 101 Book
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Description
If you're interested in learning data science, then you need to read this book! In this review, I'll give you my honest thoughts on the book and whether or not you should read it.
If you're looking for a book that will teach you all the basics of data science, then this is the book for you! The book has been designed for beginners, so whether you have no experience in data science or you're a beginner, this is the book for you! I would definitely recommend this book to anyone interested in data science!
Script:
I feel so much nostalgia looking at this book. I attribute much of my successful career in data science to this introduction to statistical learning. If you are starting from knowing nothing about machine learning this is the book to start with. It is written by giants in the field. Tibshirani was a student of Brad Efron and the inventor of the lasso. Hastie has researched non-parametrics most of his career. Daniela Witten was a student of Tibshirani and Hastie and Forbes put her on the 30 under 30 list. Gareth James was also a student of Hastie. This book does a good job holding the reader's hand through topics. It assumes the reader knows little to nothing about machine learning. The breadth of topics covered is wide. It covers linear models, classification, bagging, boosting, support vector machines, cross-validation, and many more. Each chapter ends with analytical exercises and Labs which require the reader to solve problems with R. As of 2022 there is a second edition of this book. The big changes are chapter 10 on deep learning and chapter 13 on multiple testing. Both topics are are very relevant today. I hope you enjoy this book as much as I have!
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FREE AND OPEN SOURCE SOFTWARE THAT I CURRENTLY USE:
If you're interested in learning data science, then you need to read this book! In this review, I'll give you my honest thoughts on the book and whether or not you should read it.
If you're looking for a book that will teach you all the basics of data science, then this is the book for you! The book has been designed for beginners, so whether you have no experience in data science or you're a beginner, this is the book for you! I would definitely recommend this book to anyone interested in data science!
Script:
I feel so much nostalgia looking at this book. I attribute much of my successful career in data science to this introduction to statistical learning. If you are starting from knowing nothing about machine learning this is the book to start with. It is written by giants in the field. Tibshirani was a student of Brad Efron and the inventor of the lasso. Hastie has researched non-parametrics most of his career. Daniela Witten was a student of Tibshirani and Hastie and Forbes put her on the 30 under 30 list. Gareth James was also a student of Hastie. This book does a good job holding the reader's hand through topics. It assumes the reader knows little to nothing about machine learning. The breadth of topics covered is wide. It covers linear models, classification, bagging, boosting, support vector machines, cross-validation, and many more. Each chapter ends with analytical exercises and Labs which require the reader to solve problems with R. As of 2022 there is a second edition of this book. The big changes are chapter 10 on deep learning and chapter 13 on multiple testing. Both topics are are very relevant today. I hope you enjoy this book as much as I have!
XVZFTUBE ONLINE:
FREE AND OPEN SOURCE SOFTWARE THAT I CURRENTLY USE:
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