Machine Learning Interview Guide
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Deep Learning Interviews
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Author : Shlomo Kashani
language : en
Publisher:
Release Date : 2020-12-03
Deep Learning Interviews written by Shlomo Kashani and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-12-03 with categories.
Deep Learning Interviews is home to hundreds of fully-solved problems, from a wide range of key topics in AI. It is designed to both rehearse interview or exam-specific topics and provide machine learning MSc/PhD students, and those awaiting an interview a well-organized overview of the field. The problems it poses are tough enough to cut your teeth on and to dramatically improve your skills-but they're framed within thought-provoking questions and engaging stories.
Cracking The Machine Learning Interview
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Author : Nitin Suri
language : en
Publisher: Independently Published
Release Date : 2018-12-18
Cracking The Machine Learning Interview written by Nitin Suri and has been published by Independently Published this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-12-18 with categories.
"A breakthrough in machine learning would be worth ten Microsofts." -Bill Gates Despite being one of the hottest disciplines in the Tech industry right now, Artificial Intelligence and Machine Learning remain a little elusive to most.The erratic availability of resources online makes it extremely challenging for us to delve deeper into these fields. Especially when gearing up for job interviews, most of us are at a loss due to the unavailability of a complete and uncondensed source of learning. Cracking the Machine Learning Interview Equips you with 225 of the best Machine Learning problems along with their solutions. Requires only a basic knowledge of fundamental mathematical and statistical concepts. Assists in learning the intricacies underlying Machine Learning concepts and algorithms suited to specific problems. Uniquely provides a manifold understanding of both statistical foundations and applied programming models for solving problems. Discusses key points and concrete tips for approaching real life system design problems and imparts the ability to apply them to your day to day work. This book covers all the major topics within Machine Learning which are frequently asked in the Interviews. These include: Supervised and Unsupervised Learning Classification and Regression Decision Trees Ensembles K-Nearest Neighbors Logistic Regression Support Vector Machines Neural Networks Regularization Clustering Dimensionality Reduction Feature Extraction Feature Engineering Model Evaluation Natural Language Processing Real life system design problems Mathematics and Statistics behind the Machine Learning Algorithms Various distributions and statistical tests This book can be used by students and professionals alike. It has been drafted in a way to benefit both, novices as well as individuals with substantial experience in Machine Learning. Following Cracking The Machine Learning Interview diligently would equip you to face any Machine Learning Interview.
Deep Learning And The Game Of Go
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Author : Kevin Ferguson
language : en
Publisher: Simon and Schuster
Release Date : 2019-01-06
Deep Learning And The Game Of Go written by Kevin Ferguson and has been published by Simon and Schuster this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-01-06 with Computers categories.
Summary Deep Learning and the Game of Go teaches you how to apply the power of deep learning to complex reasoning tasks by building a Go-playing AI. After exposing you to the foundations of machine and deep learning, you'll use Python to build a bot and then teach it the rules of the game. Foreword by Thore Graepel, DeepMind Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the Technology The ancient strategy game of Go is an incredible case study for AI. In 2016, a deep learning-based system shocked the Go world by defeating a world champion. Shortly after that, the upgraded AlphaGo Zero crushed the original bot by using deep reinforcement learning to master the game. Now, you can learn those same deep learning techniques by building your own Go bot! About the Book Deep Learning and the Game of Go introduces deep learning by teaching you to build a Go-winning bot. As you progress, you'll apply increasingly complex training techniques and strategies using the Python deep learning library Keras. You'll enjoy watching your bot master the game of Go, and along the way, you'll discover how to apply your new deep learning skills to a wide range of other scenarios! What's inside Build and teach a self-improving game AI Enhance classical game AI systems with deep learning Implement neural networks for deep learning About the Reader All you need are basic Python skills and high school-level math. No deep learning experience required. About the Author Max Pumperla and Kevin Ferguson are experienced deep learning specialists skilled in distributed systems and data science. Together, Max and Kevin built the open source bot BetaGo. Table of Contents PART 1 - FOUNDATIONS Toward deep learning: a machine-learning introduction Go as a machine-learning problem Implementing your first Go bot PART 2 - MACHINE LEARNING AND GAME AI Playing games with tree search Getting started with neural networks Designing a neural network for Go data Learning from data: a deep-learning bot Deploying bots in the wild Learning by practice: reinforcement learning Reinforcement learning with policy gradients Reinforcement learning with value methods Reinforcement learning with actor-critic methods PART 3 - GREATER THAN THE SUM OF ITS PARTS AlphaGo: Bringing it all together AlphaGo Zero: Integrating tree search with reinforcement learning
Ace The Data Science Interview
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Author : Kevin Huo
language : en
Publisher:
Release Date : 2021
Ace The Data Science Interview written by Kevin Huo and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021 with Big data categories.
Machine Learning Interview Guide
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Author : Rehan Guha
language : en
Publisher: BPB Publications
Release Date : 2024-12-26
Machine Learning Interview Guide written by Rehan Guha and has been published by BPB Publications this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-12-26 with Computers categories.
DESCRIPTION This book prepares you with the knowledge and skills to confidently excel in the exciting world of machine learning (ML) interviews and launch a successful career in this dynamic field. This book offers a collection of curated questions and answers to help readers understand key ML concepts, including data processing, classification, regression, clustering, dimensionality reduction, time series, and natural language processing (NLP). While not exhaustive, it focuses on critical topics and common questions often encountered in interviews. The chapters highlight essential concepts without a strict order of importance, reflecting the informal nature of ML interviews. Alongside theoretical knowledge, the book emphasizes the importance of coding and real-world application for a deeper understanding. Practical exercises, coding projects, and continuous learning are crucial to mastering ML concepts. By mastering the concepts and question-answer formats presented in this book, you will be well-prepared to tackle technical interview challenges and confidently showcase your ML expertise. This guide will help you achieve your career goals in the exciting field of ML. KEY FEATURES ● Major topics and concepts covered in a question-answer format. ● One can gain expertise in how to present an answer during an ML interview. ● Helps to structure the interview process and make it streamlined as per the industry. WHAT YOU WILL LEARN ● Understand core data concepts for ML. ● Master classification and regression algorithms. ● Learn clustering and dimensionality reduction techniques. ● Analyze and forecast time-dependent data with time series analysis. ● Gain NLP proficiency and understand human language with techniques like tokenization, stemming, lemmatization, and advanced language models. WHO THIS BOOK IS FOR This book can be used by an interviewee, interviewer, ML professionals who want to learn the interview structure, and ML practitioners who want to refresh their memory and use this book as a reference guide. Managerial and non-technical people can use this book to learn ML in unique ways through a question-answer format. TABLE OF CONTENTS 1. Data Processing for Machine Learning 2. Classification 3. Regression 4. Clustering and Dimensionality Reduction 5. Time Series 6. Natural Language Processing
500 Machine Learning Ml Interview Questions And Answers
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Author : Vamsee Puligadda
language : en
Publisher: Vamsee Puligadda
Release Date :
500 Machine Learning Ml Interview Questions And Answers written by Vamsee Puligadda and has been published by Vamsee Puligadda this book supported file pdf, txt, epub, kindle and other format this book has been release on with Computers categories.
Get that job, you aspire for! Want to switch to that high paying job? Or are you already been preparing hard to give interview the next weekend? Do you know how many people get rejected in interviews by preparing only concepts but not focusing on actually which questions will be asked in the interview? Don't be that person this time. This is the most comprehensive Machine Learning (ML) interview questions book that you can ever find out. It contains: 500 most frequently asked and important Machine Learning (ML) interview questions and answers Wide range of questions which cover not only basics in Machine Learning (ML) but also most advanced and complex questions which will help freshers, experienced professionals, senior developers, testers to crack their interviews.
Deep Learning
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Author : Shriram K Vasudevan
language : en
Publisher: CRC Press
Release Date : 2021-12-24
Deep Learning written by Shriram K Vasudevan and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-12-24 with Computers categories.
Deep Learning: A Comprehensive Guide provides comprehensive coverage of Deep Learning (DL) and Machine Learning (ML) concepts. DL and ML are the most sought-after domains, requiring a deep understanding – and this book gives no less than that. This book enables the reader to build innovative and useful applications based on ML and DL. Starting with the basics of neural networks, and continuing through the architecture of various types of CNNs, RNNs, LSTM, and more till the end of the book, each and every topic is given the utmost care and shaped professionally and comprehensively. Key Features Includes the smooth transition from ML concepts to DL concepts Line-by-line explanations have been provided for all the coding-based examples Includes a lot of real-time examples and interview questions that will prepare the reader to take up a job in ML/DL right away Even a person with a non-computer-science background can benefit from this book by following the theory, examples, case studies, and code snippets Every chapter starts with the objective and ends with a set of quiz questions to test the reader’s understanding Includes references to the related YouTube videos that provide additional guidance AI is a domain for everyone. This book is targeted toward everyone irrespective of their field of specialization. Graduates and researchers in deep learning will find this book useful.
How Smart Machines Think
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Author : Sean Gerrish
language : en
Publisher: MIT Press
Release Date : 2018-10-30
How Smart Machines Think written by Sean Gerrish and has been published by MIT Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-10-30 with Computers categories.
Everything you've always wanted to know about self-driving cars, Netflix recommendations, IBM's Watson, and video game-playing computer programs. The future is here: Self-driving cars are on the streets, an algorithm gives you movie and TV recommendations, IBM's Watson triumphed on Jeopardy over puny human brains, computer programs can be trained to play Atari games. But how do all these things work? In this book, Sean Gerrish offers an engaging and accessible overview of the breakthroughs in artificial intelligence and machine learning that have made today's machines so smart. Gerrish outlines some of the key ideas that enable intelligent machines to perceive and interact with the world. He describes the software architecture that allows self-driving cars to stay on the road and to navigate crowded urban environments; the million-dollar Netflix competition for a better recommendation engine (which had an unexpected ending); and how programmers trained computers to perform certain behaviors by offering them treats, as if they were training a dog. He explains how artificial neural networks enable computers to perceive the world—and to play Atari video games better than humans. He explains Watson's famous victory on Jeopardy, and he looks at how computers play games, describing AlphaGo and Deep Blue, which beat reigning world champions at the strategy games of Go and chess. Computers have not yet mastered everything, however; Gerrish outlines the difficulties in creating intelligent agents that can successfully play video games like StarCraft that have evaded solution—at least for now. Gerrish weaves the stories behind these breakthroughs into the narrative, introducing readers to many of the researchers involved, and keeping technical details to a minimum. Science and technology buffs will find this book an essential guide to a future in which machines can outsmart people.
Cracking The Data Science Interview
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Author : Maverick Lin
language : en
Publisher:
Release Date : 2019-12-17
Cracking The Data Science Interview written by Maverick Lin and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-12-17 with categories.
Cracking the Data Science Interview is the first book that attempts to capture the essence of data science in a concise, compact, and clean manner. In a Cracking the Coding Interview style, Cracking the Data Science Interview first introduces the relevant concepts, then presents a series of interview questions to help you solidify your understanding and prepare you for your next interview. Topics include: - Necessary Prerequisites (statistics, probability, linear algebra, and computer science) - 18 Big Ideas in Data Science (such as Occam's Razor, Overfitting, Bias/Variance Tradeoff, Cloud Computing, and Curse of Dimensionality) - Data Wrangling (exploratory data analysis, feature engineering, data cleaning and visualization) - Machine Learning Models (such as k-NN, random forests, boosting, neural networks, k-means clustering, PCA, and more) - Reinforcement Learning (Q-Learning and Deep Q-Learning) - Non-Machine Learning Tools (graph theory, ARIMA, linear programming) - Case Studies (a look at what data science means at companies like Amazon and Uber) Maverick holds a bachelor's degree from the College of Engineering at Cornell University in operations research and information engineering (ORIE) and a minor in computer science. He is the author of the popular Data Science Cheatsheet and Data Engineering Cheatsheet on GCP and has previous experience in data science consulting for a Fortune 500 company focusing on fraud analytics.
Learning How To Learn
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Author : Barbara Oakley, PhD
language : en
Publisher: Penguin
Release Date : 2018-08-07
Learning How To Learn written by Barbara Oakley, PhD and has been published by Penguin this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-08-07 with Juvenile Nonfiction categories.
A surprisingly simple way for students to master any subject--based on one of the world's most popular online courses and the bestselling book A Mind for Numbers A Mind for Numbers and its wildly popular online companion course "Learning How to Learn" have empowered more than two million learners of all ages from around the world to master subjects that they once struggled with. Fans often wish they'd discovered these learning strategies earlier and ask how they can help their kids master these skills as well. Now in this new book for kids and teens, the authors reveal how to make the most of time spent studying. We all have the tools to learn what might not seem to come naturally to us at first--the secret is to understand how the brain works so we can unlock its power. This book explains: Why sometimes letting your mind wander is an important part of the learning process How to avoid "rut think" in order to think outside the box Why having a poor memory can be a good thing The value of metaphors in developing understanding A simple, yet powerful, way to stop procrastinating Filled with illustrations, application questions, and exercises, this book makes learning easy and fun.