Grokking Algorithms
DOWNLOAD
Download Grokking Algorithms PDF/ePub or read online books in Mobi eBooks. Click Download or Read Online button to get Grokking Algorithms book now. This website allows unlimited access to, at the time of writing, more than 1.5 million titles, including hundreds of thousands of titles in various foreign languages. If the content not found or just blank you must refresh this page
Grokking Algorithms
DOWNLOAD
Author : Aditya Bhargava
language : en
Publisher: Simon and Schuster
Release Date : 2016-05-12
Grokking Algorithms written by Aditya Bhargava 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 2016-05-12 with Computers categories.
"This book does the impossible: it makes math fun and easy!" - Sander Rossel, COAS Software Systems Grokking Algorithms is a fully illustrated, friendly guide that teaches you how to apply common algorithms to the practical problems you face every day as a programmer. You'll start with sorting and searching and, as you build up your skills in thinking algorithmically, you'll tackle more complex concerns such as data compression and artificial intelligence. Each carefully presented example includes helpful diagrams and fully annotated code samples in Python. Learning about algorithms doesn't have to be boring! Get a sneak peek at the fun, illustrated, and friendly examples you'll find in Grokking Algorithms on Manning Publications' YouTube channel. Continue your journey into the world of algorithms with Algorithms in Motion, a practical, hands-on video course available exclusively at Manning.com (www.manning.com/livevideo/algorithms-?in-motion). Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the Technology An algorithm is nothing more than a step-by-step procedure for solving a problem. The algorithms you'll use most often as a programmer have already been discovered, tested, and proven. If you want to understand them but refuse to slog through dense multipage proofs, this is the book for you. This fully illustrated and engaging guide makes it easy to learn how to use the most important algorithms effectively in your own programs. About the Book Grokking Algorithms is a friendly take on this core computer science topic. In it, you'll learn how to apply common algorithms to the practical programming problems you face every day. You'll start with tasks like sorting and searching. As you build up your skills, you'll tackle more complex problems like data compression and artificial intelligence. Each carefully presented example includes helpful diagrams and fully annotated code samples in Python. By the end of this book, you will have mastered widely applicable algorithms as well as how and when to use them. What's Inside Covers search, sort, and graph algorithms Over 400 pictures with detailed walkthroughs Performance trade-offs between algorithms Python-based code samples About the Reader This easy-to-read, picture-heavy introduction is suitable for self-taught programmers, engineers, or anyone who wants to brush up on algorithms. About the Author Aditya Bhargava is a Software Engineer with a dual background in Computer Science and Fine Arts. He blogs on programming at adit.io. Table of Contents Introduction to algorithms Selection sort Recursion Quicksort Hash tables Breadth-first search Dijkstra's algorithm Greedy algorithms Dynamic programming K-nearest neighbors
Grokking Algorithms
DOWNLOAD
Author : Aditya Bhargava
language : en
Publisher:
Release Date : 2016
Grokking Algorithms written by Aditya Bhargava and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016 with Computer algorithms categories.
Grokking Artificial Intelligence Algorithms
DOWNLOAD
Author : Rishal Hurbans
language : en
Publisher: Manning
Release Date : 2020-09-01
Grokking Artificial Intelligence Algorithms written by Rishal Hurbans and has been published by Manning this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-09-01 with Computers categories.
”This book takes an impossibly broad area of computer science and communicates what working developers need to understand in a clear and thorough way.” - David Jacobs, Product Advance Local Key Features Master the core algorithms of deep learning and AI Build an intuitive understanding of AI problems and solutions Written in simple language, with lots of illustrations and hands-on examples Creative coding exercises, including building a maze puzzle game and exploring drone optimization About The Book “Artificial intelligence” requires teaching a computer how to approach different types of problems in a systematic way. The core of AI is the algorithms that the system uses to do things like identifying objects in an image, interpreting the meaning of text, or looking for patterns in data to spot fraud and other anomalies. Mastering the core algorithms for search, image recognition, and other common tasks is essential to building good AI applications Grokking Artificial Intelligence Algorithms uses illustrations, exercises, and jargon-free explanations to teach fundamental AI concepts.You’ll explore coding challenges like detecting bank fraud, creating artistic masterpieces, and setting a self-driving car in motion. All you need is the algebra you remember from high school math class and beginning programming skills. What You Will Learn Use cases for different AI algorithms Intelligent search for decision making Biologically inspired algorithms Machine learning and neural networks Reinforcement learning to build a better robot This Book Is Written For For software developers with high school–level math skills. About the Author Rishal Hurbans is a technologist, startup and AI group founder, and international speaker. Table of Contents 1 Intuition of artificial intelligence 2 Search fundamentals 3 Intelligent search 4 Evolutionary algorithms 5 Advanced evolutionary approaches 6 Swarm intelligence: Ants 7 Swarm intelligence: Particles 8 Machine learning 9 Artificial neural networks 10 Reinforcement learning with Q-learning
Grokking Machine Learning
DOWNLOAD
Author : Luis Serrano
language : en
Publisher: Simon and Schuster
Release Date : 2021-12-14
Grokking Machine Learning written by Luis Serrano 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 2021-12-14 with Computers categories.
Grokking Machine Learning presents machine learning algorithms and techniques in a way that anyone can understand. This book skips the confused academic jargon and offers clear explanations that require only basic algebra. As you go, you'll build interesting projects with Python, including models for spam detection and image recognition. You'll also pick up practical skills for cleaning and preparing data.
Grokking Deep Learning
DOWNLOAD
Author : Andrew Trask
language : en
Publisher: Manning Publications
Release Date : 2019-01-25
Grokking Deep Learning written by Andrew Trask and has been published by Manning Publications this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-01-25 with Computers categories.
Summary Grokking Deep Learning teaches you to build deep learning neural networks from scratch! In his engaging style, seasoned deep learning expert Andrew Trask shows you the science under the hood, so you grok for yourself every detail of training neural networks. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the Technology Deep learning, a branch of artificial intelligence, teaches computers to learn by using neural networks, technology inspired by the human brain. Online text translation, self-driving cars, personalized product recommendations, and virtual voice assistants are just a few of the exciting modern advancements possible thanks to deep learning. About the Book Grokking Deep Learning teaches you to build deep learning neural networks from scratch! In his engaging style, seasoned deep learning expert Andrew Trask shows you the science under the hood, so you grok for yourself every detail of training neural networks. Using only Python and its math-supporting library, NumPy, you'll train your own neural networks to see and understand images, translate text into different languages, and even write like Shakespeare! When you're done, you'll be fully prepared to move on to mastering deep learning frameworks. What's inside The science behind deep learning Building and training your own neural networks Privacy concepts, including federated learning Tips for continuing your pursuit of deep learning About the Reader For readers with high school-level math and intermediate programming skills. About the Author Andrew Trask is a PhD student at Oxford University and a research scientist at DeepMind. Previously, Andrew was a researcher and analytics product manager at Digital Reasoning, where he trained the world's largest artificial neural network and helped guide the analytics roadmap for the Synthesys cognitive computing platform. Table of Contents Introducing deep learning: why you should learn it Fundamental concepts: how do machines learn? Introduction to neural prediction: forward propagation Introduction to neural learning: gradient descent Learning multiple weights at a time: generalizing gradient descent Building your first deep neural network: introduction to backpropagation How to picture neural networks: in your head and on paper Learning signal and ignoring noise:introduction to regularization and batching Modeling probabilities and nonlinearities: activation functions Neural learning about edges and corners: intro to convolutional neural networks Neural networks that understand language: king - man + woman == ? Neural networks that write like Shakespeare: recurrent layers for variable-length data Introducing automatic optimization: let's build a deep learning framework Learning to write like Shakespeare: long short-term memory Deep learning on unseen data: introducing federated learning Where to go from here: a brief guide
Grokking Deep Reinforcement Learning
DOWNLOAD
Author : Miguel Morales
language : en
Publisher: Manning
Release Date : 2020-11-10
Grokking Deep Reinforcement Learning written by Miguel Morales and has been published by Manning this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-11-10 with Computers categories.
Grokking Deep Reinforcement Learning uses engaging exercises to teach you how to build deep learning systems. This book combines annotated Python code with intuitive explanations to explore DRL techniques. You’ll see how algorithms function and learn to develop your own DRL agents using evaluative feedback. Summary We all learn through trial and error. We avoid the things that cause us to experience pain and failure. We embrace and build on the things that give us reward and success. This common pattern is the foundation of deep reinforcement learning: building machine learning systems that explore and learn based on the responses of the environment. Grokking Deep Reinforcement Learning introduces this powerful machine learning approach, using examples, illustrations, exercises, and crystal-clear teaching. You'll love the perfectly paced teaching and the clever, engaging writing style as you dig into this awesome exploration of reinforcement learning fundamentals, effective deep learning techniques, and practical applications in this emerging field. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the technology We learn by interacting with our environment, and the rewards or punishments we experience guide our future behavior. Deep reinforcement learning brings that same natural process to artificial intelligence, analyzing results to uncover the most efficient ways forward. DRL agents can improve marketing campaigns, predict stock performance, and beat grand masters in Go and chess. About the book Grokking Deep Reinforcement Learning uses engaging exercises to teach you how to build deep learning systems. This book combines annotated Python code with intuitive explanations to explore DRL techniques. You’ll see how algorithms function and learn to develop your own DRL agents using evaluative feedback. What's inside An introduction to reinforcement learning DRL agents with human-like behaviors Applying DRL to complex situations About the reader For developers with basic deep learning experience. About the author Miguel Morales works on reinforcement learning at Lockheed Martin and is an instructor for the Georgia Institute of Technology’s Reinforcement Learning and Decision Making course. Table of Contents 1 Introduction to deep reinforcement learning 2 Mathematical foundations of reinforcement learning 3 Balancing immediate and long-term goals 4 Balancing the gathering and use of information 5 Evaluating agents’ behaviors 6 Improving agents’ behaviors 7 Achieving goals more effectively and efficiently 8 Introduction to value-based deep reinforcement learning 9 More stable value-based methods 10 Sample-efficient value-based methods 11 Policy-gradient and actor-critic methods 12 Advanced actor-critic methods 13 Toward artificial general intelligence
Computer Science Distilled
DOWNLOAD
Author : Wladston Ferreira Filho
language : en
Publisher: Code Energy
Release Date : 2017-01-17
Computer Science Distilled written by Wladston Ferreira Filho and has been published by Code Energy this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-01-17 with Computers categories.
A walkthrough of computer science concepts you must know. Designed for readers who don't care for academic formalities, it's a fast and easy computer science guide. It teaches the foundations you need to program computers effectively. After a simple introduction to discrete math, it presents common algorithms and data structures. It also outlines the principles that make computers and programming languages work.
Grokking Algorithms Second Edition
DOWNLOAD
Author : Aditya Y Bhargava
language : en
Publisher: Simon and Schuster
Release Date : 2024-04-02
Grokking Algorithms Second Edition written by Aditya Y Bhargava 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 2024-04-02 with Computers categories.
A friendly, fully-illustrated introduction to the most important computer programming algorithms. Master the most widely used algorithms and be fully prepared when you’re asked about them at your next job interview. With beautifully simple explanations, over 400 fun illustrations, and dozens of relevant examples, you’ll actually enjoy learning about algorithms with this fun and friendly guide! In Grokking Algorithms, Second Edition you will discover: Search, sort, and graph algorithms Data structures such as arrays, lists, hash tables, trees, and graphs NP-complete and greedy algorithms Performance trade-offs between algorithms Exercises and code samples in every chapter Over 400 illustrations with detailed walkthroughs The first edition of Grokking Algorithms proved to over 100,000 readers that learning algorithms doesn't have to be complicated or boring! This revised second edition contains brand new coverage of trees, including binary search trees, balanced trees, B-trees and more. You’ll also discover fresh insights on data structure performance that takes account of modern CPUs. Plus, the book’s fully annotated code samples have been updated to Python 3. Foreword by Daniel Zingaro. About the technology The algorithms you use most often have already been discovered, tested, and proven. Grokking Algorithms, Second Edition makes it a breeze to learn, understand, and use them. With beautifully simple explanations, over 400 fun illustrations, and dozens of relevant examples, it’s the perfect way to unlock the power of algorithms in your everyday work and prepare for your next coding interview—no math required! About the book Grokking Algorithms, Second Edition teaches you important algorithms to speed up your programs, simplify your code, and solve common programming problems. Start with tasks like sorting and searching, then build your skills to tackle advanced problems like data compression and artificial intelligence. You’ll even learn to compare the performance tradeoffs between algorithms. Plus, this new edition includes fresh coverage of trees, NP-complete problems, and code updates to Python 3. What's inside Search, sort, and graph algorithms Data structures such as arrays, lists, hash tables, trees, and graphs NP-complete and greedy algorithms Exercises and code samples in every chapter About the reader No advanced math or programming skills required. About the author Aditya Bhargava is a Software Engineer with a dual background in Computer Science and Fine Arts. He blogs on programming at adit.io. Table of Contents 1 Introduction to algorithms 2 Selection sort 3 Recursion 4 Quicksort 5 Hash tables 6 Beadth-first search 7 Trees 8 Balanced trees 9 Dijkstra’s algorithm 10 Greedy algorithms 11 Dynamic programming 12 k-nearest neighbors 13 where to go next
Grokking Algorithms Second Edition
DOWNLOAD
Author : Aditya Y Bhargava
language : en
Publisher: Simon and Schuster
Release Date : 2024-03-26
Grokking Algorithms Second Edition written by Aditya Y Bhargava 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 2024-03-26 with Computers categories.
A friendly, fully-illustrated introduction to the most important computer programming algorithms. Suitable for self-taught programmers, engineers, job seekers, or anyone who wants to brush up on algorithms.
Java 9 Data Structures And Algorithms
DOWNLOAD
Author : Debasish Ray Chawdhuri
language : en
Publisher: Packt Publishing Ltd
Release Date : 2017-04-28
Java 9 Data Structures And Algorithms written by Debasish Ray Chawdhuri and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-04-28 with Computers categories.
Gain a deep understanding of the complexity of data structures and algorithms and discover the right way to write more efficient code About This Book This book provides complete coverage of reactive and functional data structures Based on the latest version of Java 9, this book illustrates the impact of new features on data structures Gain exposure to important concepts such as Big-O Notation and Dynamic Programming Who This Book Is For This book is for Java developers who want to learn about data structures and algorithms. Basic knowledge of Java is assumed. What You Will Learn Understand the fundamentals of algorithms, data structures, and measurement of complexity Find out what general purpose data structures are, including arrays, linked lists, double ended linked lists, and circular lists Get a grasp on the basics of abstract data types—stack, queue, and double ended queue See how to use recursive functions and immutability while understanding and in terms of recursion Handle reactive programming and its related data structures Use binary search, sorting, and efficient sorting—quicksort and merge sort Work with the important concept of trees and list all nodes of the tree, traversal of tree, search trees, and balanced search trees Apply advanced general purpose data structures, priority queue-based sorting, and random access immutable linked lists Gain a better understanding of the concept of graphs, directed and undirected graphs, undirected trees, and much more In Detail Java 9 Data Structures and Algorithms covers classical, functional, and reactive data structures, giving you the ability to understand computational complexity, solve problems, and write efficient code. This book is based on the Zero Bug Bounce milestone of Java 9. We start off with the basics of algorithms and data structures, helping you understand the fundamentals and measure complexity. From here, we introduce you to concepts such as arrays, linked lists, as well as abstract data types such as stacks and queues. Next, we'll take you through the basics of functional programming while making sure you get used to thinking recursively. We provide plenty of examples along the way to help you understand each concept. You will get the also get a clear picture of reactive programming, binary searches, sorting, search trees, undirected graphs, and a whole lot more! Style and approach This book will teach you about all the major algorithms in a step-by-step manner. Special notes on the Big-O Notation and its impact on algorithms will give you fresh insights.