500 Machine Learning (ML) Interview Questions and Answers
Title | 500 Machine Learning (ML) Interview Questions and Answers PDF eBook |
Author | Vamsee Puligadda |
Publisher | Vamsee Puligadda |
Pages | 135 |
Release | |
Genre | Computers |
ISBN |
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 Interviews
Title | Deep Learning Interviews PDF eBook |
Author | Shlomo Kashani |
Publisher | |
Pages | |
Release | 2020-12-09 |
Genre | |
ISBN | 9781034057253 |
The book's contents is a large inventory of numerous topics relevant to DL job interviews and graduate level exams. That places this work at the forefront of the growing trend in science to teach a core set of practical mathematical and computational skills. It is widely accepted that the training of every computer scientist must include the fundamental theorems of ML, and AI appears in the curriculum of nearly every university. This volume is designed as an excellent reference for graduates of such programs.
Deep Learning and the Game of Go
Title | Deep Learning and the Game of Go PDF eBook |
Author | Kevin Ferguson |
Publisher | Simon and Schuster |
Pages | 611 |
Release | 2019-01-06 |
Genre | Computers |
ISBN | 1638354014 |
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
Title | Ace the Data Science Interview PDF eBook |
Author | Kevin Huo |
Publisher | |
Pages | 290 |
Release | 2021 |
Genre | Big data |
ISBN | 9780578973838 |
RocketPrep Ace Your Data Science Interview 300 Practice Questions and Answers: Machine Learning, Statistics, Databases and More
Title | RocketPrep Ace Your Data Science Interview 300 Practice Questions and Answers: Machine Learning, Statistics, Databases and More PDF eBook |
Author | Zack Austin |
Publisher | Lulu.com |
Pages | 119 |
Release | 2017-12-09 |
Genre | Computers |
ISBN | 138743196X |
Here's what you get in this book: - 300 practice questions and answers spanning the breadth of topics under the data science umbrella - Covers statistics, machine learning, SQL, NoSQL, Hadoop and bioinformatics - Emphasis on real-world application with a chapter on Python libraries for machine learning - Focus on the most frequently asked interview questions. Avoid information overload - Compact format: easy to read, easy to carry, so you can study on-the-go Now, you finally have what you need to crush your data science interview, and land that dream job. About The Author Zack Austin has been building large scale enterprise systems for clients in the media, telecom, financial services and publishing since 2001. He is based in New York City.
Machine Learning Interview Questions
Title | Machine Learning Interview Questions PDF eBook |
Author | Veena A and Gowrishankar S |
Publisher | Clever Fox Publishing |
Pages | 222 |
Release | |
Genre | Antiques & Collectibles |
ISBN | 9356488398 |
The book aim of Machine Learning interview questions is to determine a candidate’s level of knowledge and understanding of Machine Learning concepts, algorithms, and tools. These types of interviews are often used by employers to assess an applicant’s problem-solving skills and technical proficiency in the field. The scope of scope of this book Machine Learning interview questions can range from basic to more complex topics, such as the fundamentals of supervised and unsupervised learning, working with data sets and libraries, building ML models, and deploying and monitoring ML systems. Additionally, the interviewer may ask questions about the candidate’s experience with specific Machine Learning frameworks, data science techniques, and software engineering practices. Overall, this book helps to assess the candidate’s level of knowledge and experience in the field of Machine Learning. As such, it is important for the interviewer to ask questions that are relevant to the job and the candidate’s qualifications, as well as to provide a supportive environment where the candidate can demonstrate their skillset.
Cracking The Machine Learning Interview
Title | Cracking The Machine Learning Interview PDF eBook |
Author | Nitin Suri |
Publisher | Independently Published |
Pages | 100 |
Release | 2018-12-18 |
Genre | |
ISBN | 9781729223604 |
"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.