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No portion of this book may be reproduced in any form by means of electronic, mechanical, photocopy, recording or otherwise, including information storage and retrieval systems, without prior written permission of the author or publisher.  \nFor permission or any other information, [contact nitinsuri.705@gmail.com](contact nitinsuri.705@gmail.com).  \nAcknowledgements  \nThis book would not exist if it weren’t for my big brother, Heemanshu Suri. I shall forever be indebted to him for providing his profound insight into the field of Machine Learning. It is his proficiency in this domain, which lent to the inception of this project.  \nTo elaborate a little on his background, Heemanshu has worked for some of the major tech companies as well as Silicon Valley Startups in the Software Engineering and Data Science fields and is presently working for Microsoft in the Artificial Intelligence and Data Infrastructure Group.  \nIn addition, he founded MyyUtopia in January 2017, an interest-based hyperlocal social networking platform which makes use of an innovative Machine Learning technique to help users connect with like-minded people nearby and find local groups and events of their interests. At present, MyyUtopia is available on Google Play Store serving roughly 10,000 users.  \nThe idea behind writing this book was conceived when he was still a graduate student in Computer Sciences at the University of Wisconsin-Madison, USA, where he spent the majority of his time learning Artificial Intelligence and Machine Learning in depth. Most of the problems and their solutions, presented in this book, are a result of hours and hours of brainstorming sessions with him.  \nCRACKING THE MACHINE LEARNING INTERVIEW is a result of his experiences along with his wide-ranging interactions with other interviewers from various Silicon Valley companies ranging from early-stage startups to mid-growth companies to tech giants such as Google and Facebook. I dedicate this book to him. Thank you Big B!  \nAnother name which deserves a very special recognition is my friend, Vasundhara Tanwar. From reading early drafts to advising me on the structure of the book to making sure that it was written in a manner that was coherent, organised and engaging at the same time, her role has been pivotal in the drafting of this book. Thank you.  \nTo Nikhil Suri, for his patience in reading through various preliminary  \nversions of this book, and his vital suggestions. Thank you brother for never saying no to my numerous feedback requests and providing all the constructive criticism.  \nFinally, I would like to express my sincere gratitude to my family, friends, and everyone who motivated me throughout. Thanks for the support, the honest feedback, and for everything else that has helped to make this book possible in its current form.  \nTable of Contents  \nChapter I Introduction  \nChapter II Why Machine Learning  \nChapter III Machine Learning Workflow  \nChapter IV How this book is organized  \nChapter 5 General Machine Learning Questions  \nChapter 6 Supervised Learning  \n6.1 Classification  \n6.1.1 Decision Trees  \n6.1.2 Ensembles  \n6.1.3 K-Nearest Neighbors  \n6.1.4 Logistic Regression  \n6.1.5 Support Vector Machines  \n6.1.6 Artificial Neural Networks  \n6.2 Regression  \n6.3 Regularization  \nChapter 7 Unsupervised Learning  \n7.1 Clustering  \n7.2 Dimensionality Reduction  \nChapter 8 Data Preprocessing  \nChapter 9 Model Evaluation  \nChapter 10 Natural Language Processing  \nChapter 11 Real World Problems Chapter XII Glossary  \nChapter XIII About The Author  \nChapter I Introduction  \nCRACKING THE MACHINE LEARNING INTERVIEW is a result of my brother, Heemanshu Suri, and my own experiences along with our interactions with other interviewers from various Silicon Valley companies ranging","cbCaic0rvxQHyBjj","https://ap.wps.com/l/cbCaic0rvxQHyBjj","pdf",2459150,135,"English","# Table of Contents\n## Chapter I Introduction\n## Chapter II Why Machine Learning\n## Chapter III Machine Learning Workflow\n## Chapter IV How this book is organized\n## Chapter 5 General Machine Learning Questions\n## Chapter 6 Supervised Learning\n## Chapter 7 Unsupervised Learning\n## Chapter 8 Data Preprocessing\n## Chapter 9 Model Evaluation\n## Chapter 10 Natural Language Processing\n## Chapter 11 Real World Problems\n## Chapter XII Glossary\n## Chapter XIII About The Author","[{\"question\":\"What makes a Machine Learning interview different from a traditional software interview?\",\"answer\":\"ML interviews focus on understanding the data, the end goals such as accuracy or performance, and the preferred learning algorithm, rather than solely coding the solution.\"},{\"question\":\"Who is this book intended for?\",\"answer\":\"It targets people preparing for interviews, planning to enter the field, refreshing machine learning skills, or seeking an in-depth overview, from beginners to advanced learners.\"},{\"question\":\"How many machine learning interview questions and solutions does the book include?\",\"answer\":\"The book includes 225 of the best interview problems along with their solutions.\"}]","CRACKING THE MACHINE LEARNING INTERVIEW - 225 Machine Learning Interview Questions with Solutions | PDF",1790358849,340]