The Hitchhiker S Guide To Machine Learning Algorithms

Author : Devin Schumacher,Francis LaBounty Jr.
Publisher : SERP Media
Page : 351 pages
File Size : 50,8 Mb
Release : 2023-07-26
Category : Computers
ISBN : 8210379456XXX

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The Hitchhiker's Guide to Machine Learning Algorithms by Devin Schumacher,Francis LaBounty Jr. Pdf

Hello humans & welcome to the world of machines! Specifically, machine learning & algorithms. We are about to embark on an exciting adventure through the vast and varied landscape of algorithms that power the cutting-edge field of artificial intelligence. Machine learning is changing the world as we know it. From predicting stock market trends and diagnosing diseases to powering the virtual assistants in our smartphones and enabling self-driving cars, and picking up the slack on your online dating conversations. What makes this book unique is its structure and depth. With 100 chapters, each dedicated to a different machine learning concept, this book is designed to be your ultimate guide to the world of machine learning algorithms. Whether you are a student, a data science professional, or someone curious about machine learning, this book aims to provide a comprehensive overview that is both accessible and in-depth. The algorithms covered in this book span various categories including: Classification & Regression: Learn about algorithms like Decision Trees, Random Forests, Support Vector Machines, and Logistic Regression which are used to classify data or predict numerical values. Clustering: Discover algorithms like k-Means, Hierarchical Clustering, and DBSCAN that group data points together based on similarities. Neural Networks & Deep Learning: Dive into algorithms and architectures like Perceptrons, Convolutional Neural Networks (CNN), and Long Short-Term Memory Networks (LSTM). Optimization: Understand algorithms like Gradient Descent, Genetic Algorithms, and Particle Swarm Optimization which find the best possible solutions in different scenarios. Ensemble Methods: Explore algorithms like AdaBoost, Gradient Boosting, and Random Forests which combine the predictions of multiple models for improved accuracy. Dimensionality Reduction: Learn about algorithms like Principal Component Analysis (PCA) and t-Distributed Stochastic Neighbor Embedding (t-SNE) which reduce the number of features in a dataset while retaining important information. Reinforcement Learning: Get to know algorithms like Q-learning, Deep Q-Network (DQN), and Monte Carlo Tree Search which are used in systems that learn from their environment. Each chapter is designed as a standalone introduction to its respective algorithm. This means you can start from any chapter that catches your interest or proceed sequentially. Along with the theory, practical examples, applications, and insights into how these algorithms work under the hood are provided. This book is not just an academic endeavor but a bridge that connects theory with practical real-world applications. It's an invitation to explore, learn, and harness the power of algorithms to solve complex problems and make informed decisions. Fasten your seat belts as we dive into the mesmerizing world of machine learning algorithms. Whether you are looking to expand your knowledge, seeking inspiration, or in pursuit of technical mastery, this book should sit on your coffee table and make you look intelligent in front of all invited (and uninvited) guests.

Author : Przemys¿aw Biecek,Anna Kozak
Publisher : Scientific Foundation Smarterpoland.PL
Page : 52 pages
File Size : 53,5 Mb
Release : 2022-02-13
Category : Electronic
ISBN : 8365291126

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The Hitchhiker's Guide to Responsible Machine Learning by Przemys¿aw Biecek,Anna Kozak Pdf

This book is a unique entanglement of theory, examples and processes relevant to Responsible Machine Learning. You will find intuitions and examples for Interpretable Machine Learning (IML) and eXplainable Artificial Intelligence (XAI). Descriptions are supplemented by code snippets with examples for R with the use of randomForest, mlr3 and DALEX packages. Finally, the process is shown through a comic book describing the adventures of two characters, Beta and Bit. The interaction of these two shows the decisions that analysts often face, whether to try a different model, try another technique for exploration or look for other data -- questions like how to compare models or validate them. All examples are fully reproducible so that one can replay all adventures on a local desktop. Model development is a responsible and challenging task but also an exciting adventure. Sometimes textbooks focus only on the technical side, losing all the fun. Here we are going to have it all.

Author : Arthur Goldstuck
Publisher : Pan Macmillan South africa
Page : 193 pages
File Size : 45,6 Mb
Release : 2023-12-01
Category : Business & Economics
ISBN : 9781770108974

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The Hitchhiker’s Guide to AI by Arthur Goldstuck Pdf

For the past decade, Arthur Goldstuck has had a front-row seat to witness the remarkable rise of AI across all sectors of business and society. As generative AI becomes a household phrase and sparks hopes and fears of machines augmenting or replacing human beings, this guide offers an invaluable overview of the past, present and future of AI. The Hitchhiker’s Guide to AI is aimed at both beginners and those who consider themselves experienced or skilled at using AI. It draws on many years of direct access to global and regional leaders in using AI, from Africa to the Middle East to North America to Europe and Asia, and it provides unique perspectives on generative AI, as well as practical advice for using it. It is useful for consumers, academics, professionals and anyone in business who wants to get up to speed quickly and practically. It also entertains and inspires anyone who is curious about AI or already engaged in its possibilities. Need to understand or refine prompting? You’re in the right place. Need to prepare for the coming impact of AI on health, travel, education and business? This is the book for you.

Author : Kenneth Reitz,Tanya Schlusser
Publisher : "O'Reilly Media, Inc."
Page : 338 pages
File Size : 53,9 Mb
Release : 2016-08-30
Category : Computers
ISBN : 9781491933220

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The Hitchhiker's Guide to Python by Kenneth Reitz,Tanya Schlusser Pdf

The Hitchhiker's Guide to Python takes the journeyman Pythonista to true expertise. More than any other language, Python was created with the philosophy of simplicity and parsimony. Now 25 years old, Python has become the primary or secondary language (after SQL) for many business users. With popularity comes diversity—and possibly dilution. This guide, collaboratively written by over a hundred members of the Python community, describes best practices currently used by package and application developers. Unlike other books for this audience, The Hitchhiker’s Guide is light on reusable code and heavier on design philosophy, directing the reader to excellent sources that already exist.

Author : Joe Grant
Publisher : Unknown
Page : 158 pages
File Size : 50,6 Mb
Release : 2019-06
Category : Electronic
ISBN : 1071237217

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Deep Machine Learning by Joe Grant Pdf

Are you interested in Machine Learning? Are you fascinated by how robots work? Are you ready to open up to the dynamics of technological change?Machine Learning has been approached in a definitive manner as a subset falling under a larger set of Artificial intelligence. It majorly focuses on the aspect of learning of machines basing on the experience and predicting consequences and actions of the machines that revolve around their experience in the past.The field has made it easy for computers and machines to enact decisions that are data driven instead of explicit programming with regard to a particular task. The algorithms and programs are designed to enable machines and computers to learn by themselves. With time, they get to improve when there is an introduction of new and unique data. The learning process applies the use of training data that sustains the coming up of a model. Insertion of new data brings up predictions that are based on the model. This means that machines are given the capability to foretell on their own.The predictions are then examined closely to identify their accuracy. If accuracy receives positive feedback, then the machine learning algorithm is trained over and over again through the assistance of a data training augmented set.Machine learning tasks are broken into various wider categories. Supervised learning aims at coming up with a model that is mathematics of a data set with desired inputs and outputs. Semi-supervised learning aims at coming up with mathematical models from incomplete data training. You will realize that sample inputs miss expected/desired output in such a case.This book will help you understand more about Deep Machine Learning. In the pages of this book, you will be able to get important chapters that include: -History of Machine Learning-The Benefits-The Challenges you may Encounter-Applications of Machine Learning-Artificial Intelligence-Big Data-And much more!With such knowledge, you will be able to embrace technological advancements and be ready for the future.Get a copy of Deep Machine Learning today and get to discover the secrets into technology!

Author : Giuseppe Bonaccorso
Publisher : Packt Publishing Ltd
Page : 567 pages
File Size : 41,6 Mb
Release : 2018-05-25
Category : Computers
ISBN : 9781788625906

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Mastering Machine Learning Algorithms by Giuseppe Bonaccorso Pdf

Explore and master the most important algorithms for solving complex machine learning problems. Key Features Discover high-performing machine learning algorithms and understand how they work in depth. One-stop solution to mastering supervised, unsupervised, and semi-supervised machine learning algorithms and their implementation. Master concepts related to algorithm tuning, parameter optimization, and more Book Description Machine learning is a subset of AI that aims to make modern-day computer systems smarter and more intelligent. The real power of machine learning resides in its algorithms, which make even the most difficult things capable of being handled by machines. However, with the advancement in the technology and requirements of data, machines will have to be smarter than they are today to meet the overwhelming data needs; mastering these algorithms and using them optimally is the need of the hour. Mastering Machine Learning Algorithms is your complete guide to quickly getting to grips with popular machine learning algorithms. You will be introduced to the most widely used algorithms in supervised, unsupervised, and semi-supervised machine learning, and will learn how to use them in the best possible manner. Ranging from Bayesian models to the MCMC algorithm to Hidden Markov models, this book will teach you how to extract features from your dataset and perform dimensionality reduction by making use of Python-based libraries such as scikit-learn. You will also learn how to use Keras and TensorFlow to train effective neural networks. If you are looking for a single resource to study, implement, and solve end-to-end machine learning problems and use-cases, this is the book you need. What you will learn Explore how a ML model can be trained, optimized, and evaluated Understand how to create and learn static and dynamic probabilistic models Successfully cluster high-dimensional data and evaluate model accuracy Discover how artificial neural networks work and how to train, optimize, and validate them Work with Autoencoders and Generative Adversarial Networks Apply label spreading and propagation to large datasets Explore the most important Reinforcement Learning techniques Who this book is for This book is an ideal and relevant source of content for data science professionals who want to delve into complex machine learning algorithms, calibrate models, and improve the predictions of the trained model. A basic knowledge of machine learning is preferred to get the best out of this guide.

Author : Giuseppe Bonaccorso
Publisher : Packt Publishing Ltd
Page : 360 pages
File Size : 42,7 Mb
Release : 2017-07-24
Category : Computers
ISBN : 9781785884511

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Machine Learning Algorithms by Giuseppe Bonaccorso Pdf

Build strong foundation for entering the world of Machine Learning and data science with the help of this comprehensive guide About This Book Get started in the field of Machine Learning with the help of this solid, concept-rich, yet highly practical guide. Your one-stop solution for everything that matters in mastering the whats and whys of Machine Learning algorithms and their implementation. Get a solid foundation for your entry into Machine Learning by strengthening your roots (algorithms) with this comprehensive guide. Who This Book Is For This book is for IT professionals who want to enter the field of data science and are very new to Machine Learning. Familiarity with languages such as R and Python will be invaluable here. What You Will Learn Acquaint yourself with important elements of Machine Learning Understand the feature selection and feature engineering process Assess performance and error trade-offs for Linear Regression Build a data model and understand how it works by using different types of algorithm Learn to tune the parameters of Support Vector machines Implement clusters to a dataset Explore the concept of Natural Processing Language and Recommendation Systems Create a ML architecture from scratch. In Detail As the amount of data continues to grow at an almost incomprehensible rate, being able to understand and process data is becoming a key differentiator for competitive organizations. Machine learning applications are everywhere, from self-driving cars, spam detection, document search, and trading strategies, to speech recognition. This makes machine learning well-suited to the present-day era of Big Data and Data Science. The main challenge is how to transform data into actionable knowledge. In this book you will learn all the important Machine Learning algorithms that are commonly used in the field of data science. These algorithms can be used for supervised as well as unsupervised learning, reinforcement learning, and semi-supervised learning. A few famous algorithms that are covered in this book are Linear regression, Logistic Regression, SVM, Naive Bayes, K-Means, Random Forest, TensorFlow, and Feature engineering. In this book you will also learn how these algorithms work and their practical implementation to resolve your problems. This book will also introduce you to the Natural Processing Language and Recommendation systems, which help you run multiple algorithms simultaneously. On completion of the book you will have mastered selecting Machine Learning algorithms for clustering, classification, or regression based on for your problem. Style and approach An easy-to-follow, step-by-step guide that will help you get to grips with real -world applications of Algorithms for Machine Learning.

Author : Devin Schumacher,Francis LaBounty Jr.
Publisher : SERP
Page : 42 pages
File Size : 48,9 Mb
Release : 2023-02-25
Category : Business & Economics
ISBN : 8210379456XXX

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The Hitchhiker's Guide to ChatGPT by Devin Schumacher,Francis LaBounty Jr. Pdf

Everything You Need to Know to Get Started Using ChatGPT to VASTLY Improve Your Efficiency, Profit & ROI in Your Business Or Start a New Business, Create Additional Revenue Streams & Fully Leverage Artificial Intelligence to Make Your Life Better Artificial Intelligence is HERE! ... And there's not much "artificial" about it. Used Correctly, AI Will Help You: Produce More: With AI, you can automate repetitive and time-consuming tasks, freeing up time to focus on creative and fulfilling work. This can enhance your personal happiness and fulfillment, while increasing productivity and efficiency in the workplace. Earn More: AI can increase productivity and efficiency, leading to greater income potential. You can also use AI-powered financial management tools to better manage your finances and make better investment decisions, potentially leading to greater wealth accumulation and financial freedom. Live More: Automate menial and trivial tasks, you can create more balance in your life and spend more time on what matters most, such as family, hobbies, and personal development. This can increase overall happiness and fulfillment. Enjoy More: More time means more pursuit of your passions & interests, ultimately leading to greater fulfillment and happiness. ... And that just scratches the surface. IN THIS BOOK: Intro to AI & ChatGPT: Get ahead of the competition and transform your business with the power of AI, even if you have no prior experience or technical expertise. Unlock unlimited possibilities for your business, driving growth and success like never before. Real-life Examples for Every industry: Discover the many ways that AI can revolutionize your industry, from improving healthcare outcomes and streamlining finance to enhancing customer service and increasing productivity. Prompts: Harness the true power of AI by understanding the importance of prompts, which can help you achieve extraordinary results, from personalized customer experiences to more accurate data analysis. Prompt Engineering: Become a master of prompt engineering and create tailored prompts that make your AI-powered applications more effective and efficient - No prior engineering experience needed. Prompt Examples: Plug & play prompts you can use these examples to inspire your own winning prompts, creating a competitive edge that sets your business apart from the rest. Jailbreaking: Unleash the full potential of AI by breaking free from traditional limitations and creating innovative solutions that push the boundaries of what's possible in your industry. Tools, Extensions & Enhancements: Access a wealth of tools, extensions, and add-ons that can help you maximize the benefits of AI and ChatGPT, driving greater results and generating more revenue - no technical knowledge required. Access to a community of experts: Get support and guidance from a community of AI and ChatGPT experts, helping you overcome challenges and make the most of this transformative technology - practically instantly. Ensure your business is always on the cutting edge of AI innovation. Hundreds of business use cases & ideas for making money with ChatGPT: Tap into an endless supply of ideas and strategies for using ChatGPT to grow your business and generate more revenue, from optimizing workflows and increasing productivity to creating personalized customer experiences and increasing sales.

Author : Joe Grant
Publisher : Deep Machine Learning
Page : 0 pages
File Size : 52,6 Mb
Release : 2023-07-06
Category : Electronic
ISBN : 1088209696

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Deep Machine Learning by Joe Grant Pdf

Learn machine algorithms using deep machine learning techniques and methods with sample codes

Author : Giuseppe Bonaccorso
Publisher : Unknown
Page : 128 pages
File Size : 43,6 Mb
Release : 2017
Category : Computer algorithms
ISBN : 1523112212

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Machine Learning Algorithms by Giuseppe Bonaccorso Pdf

Author : Steven Cooper
Publisher : Roland Bind
Page : 85 pages
File Size : 43,6 Mb
Release : 2018-09-07
Category : Computers
ISBN : PKEY:6610000102952

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Machine Learning for Beginners by Steven Cooper Pdf

If you are looking for a complete beginners guide to learn machine learning with examples, in just a few hours, then you need to continue reading. Machine learning is an incredibly dense topic. It's hard to imagine condensing it into an easily readable and digestible format. However, this book aims to do exactly that. ★★ Grab your copy today and learn ★★ ♦ The different types of learning algorithm that you can expect to encounter ♦ The numerous applications of machine learning ♦ The different types of machine learning and how they differ ♦ The best practices for picking up machine learning ♦ What languages and libraries to work with ♦ The future of machine learning ♦ The various problems that you can solve with machine learning algorithms ♦ And much more... Starting from nothing, we slowly work our way through all the concepts that are central to machine learning. By the end of this book, you're going to feel as though you have an extremely firm understanding of what machine learning is, how it can be used, and most importantly, how it can change the world. You're also going to have an understanding of the logic behind the algorithms and what they aim to accomplish. Don't waste your time working with a book that's only going to make an already complicated topic even more complicated. Scroll up and click the buy now button to learn everything you need to know about Machine Learning!

Author : Ryan Knight
Publisher : Ryan Knight
Page : 48 pages
File Size : 40,8 Mb
Release : 2024-05-08
Category : Computers
ISBN : 8210379456XXX

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Machine Learning for Beginners by Ryan Knight Pdf

Enter a world of algorithms, data, and artificial intelligence, this all-inclusive guide strips away the complexity of machine learning and AI, transforming them from daunting subjects into accessible and comprehendible concepts. Whether you're a total novice or a professional looking to broaden your knowledge, this guide provides a structured approach that walks you through the basics, right through to the cutting-edge applications of AI and machine learning. Crafted with the reader in mind, every chapter provides detailed explanations, relatable examples, and step-by-step instructions to ensure a comprehensive yet enjoyable learning experience. Inside this book, you'll discover: An introduction to the exciting world of machine learning and AI, making it accessible to everyone regardless of technical background. Comprehensive discussions on the foundational concepts of machine learning, including algorithms, data science principles, and the different types of machine learning. Deep dives into the transformative applications of AI and machine learning in industries such as healthcare, retail, finance, transportation, education, and entertainment. Practical guides on mastering the essential tools and techniques for building intelligent solutions, complete with hands-on exercises and examples. An exploration of the ethical considerations around AI and machine learning, and the responsibilities we have as practitioners. Future trends in machine learning and AI, providing a glimpse into what lies on the horizon. Ignite your journey into the fascinating world of machine learning and AI today. Unleash the power of data and algorithms, create intelligent solutions, and shape a better future. Are you ready to master the future? The opportunity is just a click away. Pick up your copy now, and let's get started!

Author : John Paul Mueller,Luca Massaron
Publisher : John Wiley & Sons
Page : 432 pages
File Size : 48,7 Mb
Release : 2016-05-31
Category : Computers
ISBN : 9781119245513

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Machine Learning For Dummies by John Paul Mueller,Luca Massaron Pdf

Your no-nonsense guide to making sense of machine learning Machine learning can be a mind-boggling concept for the masses, but those who are in the trenches of computer programming know just how invaluable it is. Without machine learning, fraud detection, web search results, real-time ads on web pages, credit scoring, automation, and email spam filtering wouldn't be possible, and this is only showcasing just a few of its capabilities. Written by two data science experts, Machine Learning For Dummies offers a much-needed entry point for anyone looking to use machine learning to accomplish practical tasks. Covering the entry-level topics needed to get you familiar with the basic concepts of machine learning, this guide quickly helps you make sense of the programming languages and tools you need to turn machine learning-based tasks into a reality. Whether you're maddened by the math behind machine learning, apprehensive about AI, perplexed by preprocessing data—or anything in between—this guide makes it easier to understand and implement machine learning seamlessly. Grasp how day-to-day activities are powered by machine learning Learn to 'speak' certain languages, such as Python and R, to teach machines to perform pattern-oriented tasks and data analysis Learn to code in R using R Studio Find out how to code in Python using Anaconda Dive into this complete beginner's guide so you are armed with all you need to know about machine learning!

Author : Ethem Mining
Publisher : Unknown
Page : 222 pages
File Size : 54,6 Mb
Release : 2019-12-03
Category : Electronic
ISBN : 1671268423

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Machine Learning for Beginners by Ethem Mining Pdf

Are you fascinated about machine learning and AI and you don't know where to start? Have you ever heard people talking about Machine Learning but you only have a vague idea of the actual meaning? Do you want to understand how machine learning could simplify your daily life? Imagine a world where computing systems understand people and the world around us them to a point where they can notice patterns, collect data, interpret it and give recommendations to solve real world problems with high level of precision. It sounds like science fiction but it is happening in healthcare, agriculture, cyber security, facial recognition, targeting and retargeting customers in online advertising, recommending specific products, stories, videos, text etc., self-driving cars, real time pricing, predicting human behavior and much more. Now imagine you being one of the people behind the code; the people who get these advanced systems to work the way they do. Would it be a dream come true for you? By virtue that you are reading this, it is clear that you have some special liking for this advanced tech and would want to learn how you can be one of the people behind the code. Even if not, you probably want to be able to understand the inner workings of these systems. The concept may sound extremely out there and advanced but it won't be if you follow this guide, which takes an easy to follow, beginner friendly language to help you to understand the ins and outs of machine learning! Here is a summary of what this book will teach you: The basics of machine learning, including what it is, how machine learning has evolved over the years, the application of machine learning in today's world and the future of machine learning How machine learning is beneficial in today's world The different approaches to machine learning, including unsupervised, supervised, reinforcement learning method, semi-supervised machine learning and many others The concept of big data analysis, including what is big data, why big data is important, the application of big data in today's world as well as the different data analysis tools that you can use The link between big data and machine learning The different machine learning algorithms, including what machine-learning algorithms are and how and when the different learning algorithms are used The concept of artificial neural networks, including how they work, when to use neural networks and more How decision trees are used in machine learning, including what decision trees are (in respect to machine learning), how they work, how the decision tree is read, the different nodes in decision trees and when to use them The ins and outs of linear and logistic regression in machine learning, including what linear regression is, different types of regression, how linear regression works, how linear regression is used and much more And much more! Even if this is your first encounter with the concept of machine learning, this book will uncover everything you need to know to master machine learning and possibly get started in this field of advanced computing knowing very well what you are venturing into. And the good thing is that the book takes a beginner friendly approach to help you to apply what you learn right away! Would You Like To Know More? Click Buy Now With 1-Click or Buy Now to get started!

Author : ML & AI ACADEMY
Publisher : Giale Limited
Page : 228 pages
File Size : 48,8 Mb
Release : 2020-11-21
Category : Electronic
ISBN : 1801255326

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Machine Learning Math by ML & AI ACADEMY Pdf

Are you looking for a complete guide of machine learning? Then keep reading... In this book, you will learn about the OpenAI Gym, used in reinforcement learning projects with several examples of the training platform provided out of the box. Machine Learning Math is the book most readers will want to have when starting to learn machine learning. This book is a reference, something you can keep coming back to hence suitable for newbies. The book is perfect for all people who have a desire to study data science. Have you heard of machine learning being everywhere, and you intend to understand what it can do? Or are you familiar with applying the tools of machine learning, but you want to make sure you aren't missing any? Having a little knowledge about mathematics, statistics, and probability would be helpful, but this book has been written in such a way that you will get most of this knowledge as you continue reading. You should not shy away from reading the book if you have no background in machine learning. You will learn how to use reinforcement learning algorithms in other tasks, for example, the board game Go, and generating deep image classifiers. This will help you to get a comprehensive understanding of reinforcement learning and help you solve real-world problems. The most interesting part of this book is the asynchronous reinforcement learning framework. You will learn what the shortcomings of DQN are, and why DQN is challenging to apply in complex tasks. Then, you will learn how to apply the asynchronous reinforcement learning framework in the actor-critic method REINFORCE, which led us to the A3C algorithm. You will learn four important things. The first one is how to implement games using gym and how to play games for relaxation and having fun. The second one is that you will learn how to preprocess data in reinforcement learning tasks such as in computer games. For practical machine learning applications, you will spend a great deal of time understanding and refining data, which affects the performance of an AI system a lot. The third one is the deep Q-learning algorithm. You will learn the intuition behind it, for example, why the replay memory is necessary, why the target network is needed, where the update rule comes from, and so on. The final one is that you will learn how to implement DQN using TensorFlow and how to visualize the training process. The following is a glimpse of what you will find inside the book: Introduction to machine learning The best machine learning algorithms Regression (a problem of predicting a real-valued label) and classification( a problem of automatically assigning a label to unlabeled example-for example spam detection) Reinforcement learning Robotics Supervised and Unsupervised learning How to implement a convolutional neural network(usually used for images) in TensorFlow Deep Learning Data preparation and processing TensorFlow machine learning frameworks Neural Networks (a combination of linear and non-linear functions) Clustering(aims to group similar samples together) Even if you have never studied Machine Learning before, you can learn it quickly. So what are you waiting for? Go to the top of the page and click Buy Now!