Bøger af Mark Liu

May 11, 1997, was a watershed moment in the history of artificial intelligence (AI): the IBM supercomputer chess engine, Deep Blue, beat the world Chess champion, Garry Kasparov. It was the first time a machine had triumphed over a human player in a Chess tournament. Fast forward 19 years to May 9, 2016, DeepMind's AlphaGo beat the world Go champion Lee Sedol. AI again stole the spotlight and generated a media frenzy. This time, a new type of AI algorithm, namely machine learning (ML) was the driving force behind the game strategies.What exactly is ML? How is it related to AI? Why is deep learning (DL) so popular these days? This book explains how traditional rule-based AI and ML work and how they can be implemented in everyday games such as Last Coin standing, Tic Tac Toe, or Connect Four. Game rules in these three games are easy to implement. As a result, readers will learn rule-based AI, deep reinforcement learning, and more importantly, how to combine the two to create powerful game strategies (the whole is indeed greater than the sum of its parts) without getting bogged down in complicated game rules.Implementing rule-based AI and ML in these straightforward games is quick and not computationally intensive. Consequently, game strategies can be trained in mere minutes or hours without requiring GPU training or supercomputing facilities, showcasing AI's ability to achieve superhuman performance in these games. More importantly, readers will gain a thorough understanding of the principles behind rule-based AI, such as the MiniMax algorithm, alpha-beta pruning, and Monte Carlo Tree Search (MCTS), and how to integrate them with cutting-edge ML techniques like convolutional neural networks and deep reinforcement learning to apply them in their own business fields and tackle real-world challenges.Written with clarity from the ground up, this book appeals to both general readers and industry professionals who seek to learn about rule-based AI and deep reinforcement learning, as well as students and educators in computer science and programming courses.

The release of ChatGPT has kicked off an arms race in Machine Learning (ML), however ML has also been described as a black box and very hard to understand. Machine Learning, Animated eases you into basic ML concepts and summarizes the learning process in three words: initialize, adjust and repeat. This is illustrated step by step with animation to show how machines learn: from initial parameter values to adjusting each step, to the final converged parameters and predictions.This book teaches readers to create their own neural networks with dense and convolutional layers, and use them to make binary and multi-category classifications. Readers will learn how to build deep learning game strategies and combine this with reinforcement learning, witnessing AI achieve super-human performance in Atari games such as Breakout, Space Invaders, Seaquest and Beam Rider.Written in a clear and concise style, illustrated with animations and images, this book is particularly appealing to readers with no background in computer science, mathematics or statistics.Access the book's repository at: https: //github.com/markhliu/MLA

A project-based book that teaches beginning Python programmers how to build working, useful, and fun voice-controlled applications. This fun, hands-on book will take your basic Python skills to the next level as you build voice-controlled apps to use in your daily life. Starting with a Python refresher and an introduction to speech-recognition/text-to-speech functionalities, you’ll soon ease into more advanced topics, like making your own modules and building working voice-controlled apps. Each chapter scaffolds multiple projects that allow you to see real results from your code at a manageable pace, while end-of-chapter exercises strengthen your understanding of new concepts. You’ll design interactive games, like Connect Four and Tic-Tac-Toe, and create intelligent computer opponents that talk and take commands; you’ll make a real-time language translator, and create voice-activated financial-market apps that track the stocks or cryptocurrencies you are interested in. Finally, you’ll load all of these features into the ultimate virtual personal assistant – a conversational VPA that tells jokes, reads the news, and gives you hands-free control of your email, browser, music player, desktop files, and more. Along the way, you’ll learn how to:●     Build Python modules, implement animations, and integrate live data into an app●     Use web-scraping skills for voice-controlling podcasts, videos, and web searches●     Fine-tune the speech recognition to accept a variety of input●     Associate regular tasks like opening files and accessing the web with speech commands●     Integrate functionality from other programs into a single VPA with computational knowledge engines to answer almost any question Packed with cross-platform code examples to download, practice activities and exercises, and explainer images, you’ll quickly become proficient in Python coding in general and speech recognition/text to speech in particular.