Data Science From Scratch 2Nd Edition Pdf Github
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Python is perhaps the most popular language for data science, largely because it is so easy to deploy code across platforms. This book focuses on Python, but everything we do is equally applicable to R. We hope that you find the book useful as you master the data science techniques that will help you analyze your data and gain insight into what it is telling you. We also hope that you gain a deeper understanding of the various tools that can help you implement your data science techniques across a variety of platforms, including Windows, Mac, and Linux.
To enable you to control what you experience in the book, we have opted to use R Markdown (Wickham and Roger 2009). R Markdown is a tool that allows authors to create a document that is then compiled into a PDF or HTML version. The result is a document that will allow you to navigate the book with just a single click. In addition, the code and output from each example are embedded in the documentation, allowing you to see the results of your own code and track the logic you follow as you read the book.
Data is the means to explore these questions and more. If they can be measured, they can be found. Then again, what? In this book, Stephens-Davidowitz illuminates the hows, whys and hows of data, and how to both make sense of and make use of it.
In addition, as we're writing an introductory book for a new community, we recognize that this book will not be perfect. We welcome any feedback from the readership on our approach to machine learning, on our text, and on any other areas of the book that we feel could be improved.
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