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Book Synopsis Deep Learning Interviews by : Shlomo Kashani
Download or read book Deep Learning Interviews written by Shlomo Kashani and published by . This book was released on 2020-12-09 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Cracking The Machine Learning Interview by : Nitin Suri
Download or read book Cracking The Machine Learning Interview written by Nitin Suri and published by Independently Published. This book was released on 2018-12-18 with total page 100 pages. Available in PDF, EPUB and Kindle. Book excerpt: "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.
Book Synopsis Artificial Intelligence Interview Questions & Answers by : Manish Soni
Download or read book Artificial Intelligence Interview Questions & Answers written by Manish Soni and published by . This book was released on 2024-11-17 with total page 189 pages. Available in PDF, EPUB and Kindle. Book excerpt: "Artificial Intelligence Interview Questions and Answers," a comprehensive guide designed to prepare both freshers and experienced professionals for the dynamic and challenging world of AI interviews. This book is meticulously curated to equip you with the necessary knowledge, strategies, and insights to excel in interviews focused on artificial intelligence, spanning a broad range of industries and technical depths.
Book Synopsis 500 Artificial Intelligence (AI) Interview Questions and Answers by : Vamsee Puligadda
Download or read book 500 Artificial Intelligence (AI) Interview Questions and Answers written by Vamsee Puligadda and published by Vamsee Puligadda. This book was released on with total page 119 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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 Artificial Intelligence (AI) interview questions book that you can ever find out. It contains: 500 most frequently asked and important Artificial Intelligence (AI) interview questions and answers Wide range of questions which cover not only basics in Artificial Intelligence (AI) but also most advanced and complex questions which will help freshers, experienced professionals, senior developers, testers to crack their interviews.
Book Synopsis 500 Machine Learning (ML) Interview Questions and Answers by : Vamsee Puligadda
Download or read book 500 Machine Learning (ML) Interview Questions and Answers written by Vamsee Puligadda and published by Vamsee Puligadda. This book was released on with total page 135 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Deep Learning and the Game of Go by : Kevin Ferguson
Download or read book Deep Learning and the Game of Go written by Kevin Ferguson and published by Simon and Schuster. This book was released on 2019-01-06 with total page 611 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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
Book Synopsis Artificial Intelligence with Python by : Prateek Joshi
Download or read book Artificial Intelligence with Python written by Prateek Joshi and published by Packt Publishing Ltd. This book was released on 2017-01-27 with total page 437 pages. Available in PDF, EPUB and Kindle. Book excerpt: Build real-world Artificial Intelligence applications with Python to intelligently interact with the world around you About This Book Step into the amazing world of intelligent apps using this comprehensive guide Enter the world of Artificial Intelligence, explore it, and create your own applications Work through simple yet insightful examples that will get you up and running with Artificial Intelligence in no time Who This Book Is For This book is for Python developers who want to build real-world Artificial Intelligence applications. This book is friendly to Python beginners, but being familiar with Python would be useful to play around with the code. It will also be useful for experienced Python programmers who are looking to use Artificial Intelligence techniques in their existing technology stacks. What You Will Learn Realize different classification and regression techniques Understand the concept of clustering and how to use it to automatically segment data See how to build an intelligent recommender system Understand logic programming and how to use it Build automatic speech recognition systems Understand the basics of heuristic search and genetic programming Develop games using Artificial Intelligence Learn how reinforcement learning works Discover how to build intelligent applications centered on images, text, and time series data See how to use deep learning algorithms and build applications based on it In Detail Artificial Intelligence is becoming increasingly relevant in the modern world where everything is driven by technology and data. It is used extensively across many fields such as search engines, image recognition, robotics, finance, and so on. We will explore various real-world scenarios in this book and you'll learn about various algorithms that can be used to build Artificial Intelligence applications. During the course of this book, you will find out how to make informed decisions about what algorithms to use in a given context. Starting from the basics of Artificial Intelligence, you will learn how to develop various building blocks using different data mining techniques. You will see how to implement different algorithms to get the best possible results, and will understand how to apply them to real-world scenarios. If you want to add an intelligence layer to any application that's based on images, text, stock market, or some other form of data, this exciting book on Artificial Intelligence will definitely be your guide! Style and approach This highly practical book will show you how to implement Artificial Intelligence. The book provides multiple examples enabling you to create smart applications to meet the needs of your organization. In every chapter, we explain an algorithm, implement it, and then build a smart application.
Book Synopsis The Sentient Machine by : Amir Husain
Download or read book The Sentient Machine written by Amir Husain and published by Simon and Schuster. This book was released on 2017-11-21 with total page 224 pages. Available in PDF, EPUB and Kindle. Book excerpt: Explores universal questions about humanity's capacity for living and thriving in the coming age of sentient machines and AI, examining debates from opposing perspectives while discussing emerging intellectual diversity and its potential role in enabling a positive life.
Book Synopsis How Smart Machines Think by : Sean Gerrish
Download or read book How Smart Machines Think written by Sean Gerrish and published by MIT Press. This book was released on 2018-10-30 with total page 313 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis A Collection of Advanced Data Science and Machine Learning Interview Questions Solved in Python and Spark (Ii) by : Antonio Gulli
Download or read book A Collection of Advanced Data Science and Machine Learning Interview Questions Solved in Python and Spark (Ii) written by Antonio Gulli and published by Createspace Independent Publishing Platform. This book was released on 2015-11-18 with total page 106 pages. Available in PDF, EPUB and Kindle. Book excerpt: A collection of Machine Learning interview questions in Python and Spark
Book Synopsis Python Machine Learning by : Sebastian Raschka
Download or read book Python Machine Learning written by Sebastian Raschka and published by Packt Publishing Ltd. This book was released on 2015-09-23 with total page 455 pages. Available in PDF, EPUB and Kindle. Book excerpt: Unlock deeper insights into Machine Leaning with this vital guide to cutting-edge predictive analytics About This Book Leverage Python's most powerful open-source libraries for deep learning, data wrangling, and data visualization Learn effective strategies and best practices to improve and optimize machine learning systems and algorithms Ask – and answer – tough questions of your data with robust statistical models, built for a range of datasets Who This Book Is For If you want to find out how to use Python to start answering critical questions of your data, pick up Python Machine Learning – whether you want to get started from scratch or want to extend your data science knowledge, this is an essential and unmissable resource. What You Will Learn Explore how to use different machine learning models to ask different questions of your data Learn how to build neural networks using Keras and Theano Find out how to write clean and elegant Python code that will optimize the strength of your algorithms Discover how to embed your machine learning model in a web application for increased accessibility Predict continuous target outcomes using regression analysis Uncover hidden patterns and structures in data with clustering Organize data using effective pre-processing techniques Get to grips with sentiment analysis to delve deeper into textual and social media data In Detail Machine learning and predictive analytics are transforming the way businesses and other organizations operate. Being able to understand trends and patterns in complex data is critical to success, becoming one of the key strategies for unlocking growth in a challenging contemporary marketplace. Python can help you deliver key insights into your data – its unique capabilities as a language let you build sophisticated algorithms and statistical models that can reveal new perspectives and answer key questions that are vital for success. Python Machine Learning gives you access to the world of predictive analytics and demonstrates why Python is one of the world's leading data science languages. If you want to ask better questions of data, or need to improve and extend the capabilities of your machine learning systems, this practical data science book is invaluable. Covering a wide range of powerful Python libraries, including scikit-learn, Theano, and Keras, and featuring guidance and tips on everything from sentiment analysis to neural networks, you'll soon be able to answer some of the most important questions facing you and your organization. Style and approach Python Machine Learning connects the fundamental theoretical principles behind machine learning to their practical application in a way that focuses you on asking and answering the right questions. It walks you through the key elements of Python and its powerful machine learning libraries, while demonstrating how to get to grips with a range of statistical models.
Book Synopsis Artificial Intelligence Tools Book by : Manish Soni
Download or read book Artificial Intelligence Tools Book written by Manish Soni and published by . This book was released on 2024-11-17 with total page 295 pages. Available in PDF, EPUB and Kindle. Book excerpt: Welcome to the exciting and rapidly evolving world of artificial intelligence (AI). This book, "Artificial Intelligence Tools: Unlocking the Power of Intelligent Systems," is designed to be your comprehensive guide to understanding, implementing, and leveraging the cutting-edge tools that drive the advancements in AI. Whether you are a seasoned professional in the field or a curious newcomer, this book aims to provide you with valuable insights and practical knowledge to navigate the multifaceted landscape of AI tools. From machine learning algorithms to neural networks, readers will gain insights into the core concepts that form the backbone of intelligent systems. We aim to make complex ideas accessible, ensuring that readers, regardless of their technical background, can grasp the essentials of AI.
Book Synopsis Machine Learning Bookcamp by : Alexey Grigorev
Download or read book Machine Learning Bookcamp written by Alexey Grigorev and published by Simon and Schuster. This book was released on 2021-11-23 with total page 470 pages. Available in PDF, EPUB and Kindle. Book excerpt: The only way to learn is to practice! In Machine Learning Bookcamp, you''ll create and deploy Python-based machine learning models for a variety of increasingly challenging projects. Taking you from the basics of machine learning to complex applications such as image and text analysis, each new project builds on what you''ve learned in previous chapters. By the end of the bookcamp, you''ll have built a portfolio of business-relevant machine learning projects that hiring managers will be excited to see. about the technology Machine learning is an analysis technique for predicting trends and relationships based on historical data. As ML has matured as a discipline, an established set of algorithms has emerged for tackling a wide range of analysis tasks in business and research. By practicing the most important algorithms and techniques, you can quickly gain a footing in this important area. Luckily, that''s exactly what you''ll be doing in Machine Learning Bookcamp. about the book In Machine Learning Bookcamp you''ll learn the essentials of machine learning by completing a carefully designed set of real-world projects. Beginning as a novice, you''ll start with the basic concepts of ML before tackling your first challenge: creating a car price predictor using linear regression algorithms. You''ll then advance through increasingly difficult projects, developing your skills to build a churn prediction application, a flight delay calculator, an image classifier, and more. When you''re done working through these fun and informative projects, you''ll have a comprehensive machine learning skill set you can apply to practical on-the-job problems. what''s inside Code fundamental ML algorithms from scratch Collect and clean data for training models Use popular Python tools, including NumPy, Pandas, Scikit-Learn, and TensorFlow Apply ML to complex datasets with images and text Deploy ML models to a production-ready environment about the reader For readers with existing programming skills. No previous machine learning experience required. about the author Alexey Grigorev has more than ten years of experience as a software engineer, and has spent the last six years focused on machine learning. Currently, he works as a lead data scientist at the OLX Group, where he deals with content moderation and image models. He is the author of two other books on using Java for data science and TensorFlow for deep learning.
Download or read book Originals written by Adam Grant and published by Penguin. This book was released on 2017-02-07 with total page 353 pages. Available in PDF, EPUB and Kindle. Book excerpt: The #1 New York Times bestseller that examines how people can champion new ideas in their careers and everyday life—and how leaders can fight groupthink, from the author of Hidden Potential, Think Again, and the co-author of Option B “Filled with fresh insights on a broad array of topics that are important to our personal and professional lives.”—The New York Times DealBook “Originals is one of the most important and captivating books I have ever read, full of surprising and powerful ideas. It will not only change the way you see the world; it might just change the way you live your life. And it could very well inspire you to change your world.” —Sheryl Sandberg, COO of Facebook and author of Lean In With Give and Take, Adam Grant not only introduced a landmark new paradigm for success but also established himself as one of his generation’s most compelling and provocative thought leaders. In Originals he again addresses the challenge of improving the world, but now from the perspective of becoming original: choosing to champion novel ideas and values that go against the grain, battle conformity, and buck outdated traditions. How can we originate new ideas, policies, and practices without risking it all? Using surprising studies and stories spanning business, politics, sports, and entertainment, Grant explores how to recognize a good idea, speak up without getting silenced, build a coalition of allies, choose the right time to act, and manage fear and doubt; how parents and teachers can nurture originality in children; and how leaders can build cultures that welcome dissent. Learn from an entrepreneur who pitches his start-ups by highlighting the reasons not to invest, a woman at Apple who challenged Steve Jobs from three levels below, an analyst who overturned the rule of secrecy at the CIA, a billionaire financial wizard who fires employees for failing to criticize him, and a TV executive who didn’t even work in comedy but saved Seinfeld from the cutting-room floor. The payoff is a set of groundbreaking insights about rejecting conformity and improving the status quo.
Download or read book The Atlas of AI written by Kate Crawford and published by Yale University Press. This book was released on 2021-04-06 with total page 336 pages. Available in PDF, EPUB and Kindle. Book excerpt: The hidden costs of artificial intelligence, from natural resources and labor to privacy and freedom What happens when artificial intelligence saturates political life and depletes the planet? How is AI shaping our understanding of ourselves and our societies? In this book Kate Crawford reveals how this planetary network is fueling a shift toward undemocratic governance and increased inequality. Drawing on more than a decade of research, award-winning science, and technology, Crawford reveals how AI is a technology of extraction: from the energy and minerals needed to build and sustain its infrastructure, to the exploited workers behind "automated" services, to the data AI collects from us. Rather than taking a narrow focus on code and algorithms, Crawford offers us a political and a material perspective on what it takes to make artificial intelligence and where it goes wrong. While technical systems present a veneer of objectivity, they are always systems of power. This is an urgent account of what is at stake as technology companies use artificial intelligence to reshape the world.
Book Synopsis Python Machine Learning by : Ryan Turner
Download or read book Python Machine Learning written by Ryan Turner and published by Publishing Factory . This book was released on 2020-04-18 with total page 185 pages. Available in PDF, EPUB and Kindle. Book excerpt: Are you a novice programmer who wants to learn Python Machine Learning? Are you worried about how to translate what you already know into Python? This book will help you overcome those problems! As machines get ever more complex and perform more and more tasks to free up our time, so it is that new ideas are developed to help us continually improve their speed and abilities. One of these is Python and in Python Machine Learning: 3 books in 1 - The Ultimate Beginner's Guide to Learn Python Machine Learning Step by Step using Scikit-Learn and Tensorflow, you will discover information and advice on: Book 1 • What machine learning is • The history of machine learning • Approaches to machine learning • Support vector machines • Machine learning and neural networks • The Internet of Things (IoT) • The future of machine learning • And more… Book 2 • The principles surrounding Python • Different types of networks so you can choose what works best for you • Features of the system • Real world feature engineering • Understanding the techniques of semi-supervised learning • And more… Book 3 • How advanced tensorflow can be used • Neural network models and how to get the most from them • Machine learning with Generative Adversarial Networks • Translating images with cross domain GANs • TF clusters and how to use them • How to debug TF models • And more… This book has been written specifically for beginners and the simple, step by step instructions and plain language make it an ideal place to start for anyone who has a passing interest in this fascinating subject. Python really is an amazing system and can provide you with endless possibilities when you start learning about it. Get a copy of Python Machine Learning today and see where the future lies.
Download or read book Learn or Die written by Edward D. Hess and published by Columbia University Press. This book was released on 2014-09-30 with total page 281 pages. Available in PDF, EPUB and Kindle. Book excerpt: To compete with today's increasing globalization and rapidly evolving technologies, individuals and organizations must take their ability to learn—the foundation for continuous improvement, operational excellence, and innovation—to a much higher level. In Learn or Die, Edward D. Hess combines recent advances in neuroscience, psychology, behavioral economics, and education with key research on high-performance businesses to create an actionable blueprint for becoming a leading-edge learning organization. Learn or Die examines the process of learning from an individual and an organizational standpoint. From an individual perspective, the book discusses the cognitive, emotional, motivational, attitudinal, and behavioral factors that promote better learning. Organizationally, Learn or Die focuses on the kinds of structures, culture, leadership, employee learning behaviors, and human resource policies that are necessary to create an environment that enables critical and innovative thinking, learning conversations, and collaboration. The volume also provides strategies to mitigate the reality that humans can be reflexive, lazy thinkers who seek confirmation of what they believe to be true and affirmation of their self-image. Exemplar learning organizations discussed include the secretive Bridgewater Associates, LP; Intuit, Inc.; United Parcel Service (UPS); W. L. Gore & Associates; and IDEO.
