Approaching (almost) any machine learning problem_abhishek thakur.pdf

Approaching (Almost) Any Machine Learning Problem 1 Approaching (Almost) Any Machine Learning Problem ISBN: 978-82-692115-2-8 Approaching (Almost) Any Machine Learning Problem 2 It would not have been possible for me to write this book without the support of my family and friends. I would also like to thank the reviewers who selflessly devoted their time in reviewing this book (names in alphabetical order). Aakash Nain Aditya Soni Andreas Müller Andrey Lukyanenko Ayon Roy Bojan Tunguz Gilberto Titericz Jr. Konrad Banachewicz Luca Massaron Nabajeet Barman Parul Pandey Ram Ramrakhya Sanyam Bhutani Sudalai Rajkumar Tanishq Abraham Walter Reade Yuval Reina I hope I did not miss anyone. Approaching (Almost) Any Machine Learning Problem 3 Before you start, there are a few things that you must be aware of while going through this book. This is not a traditional book. The book expects you to have basic knowledge of machine learning and deep learning. Important terms are bold. Variable names and function/class names are italic. ═════════════════════════════════════════════════════════════════════════ All the code is between these two lines ═════════════════════════════════════════════════════════════════════════ Most of the times, the output is provided right after the code blocks. Figures are locally defined. For example, figure 1 is the first figure Code is very important in this book and there is a lot of it. You must go through the code carefully and implement it on your own if you want to understand what’s going on. Comments in Python begin with a hash (#). All the code in this book is explained line-by-line only using comments. Thus, these comments must not be ignored. Bash commands start with $ or ❯. If you find a pirated copy of this book (print or e-book or pdf), contact me directly with the details so that I can take necessary ac