Science Machine Learning

The author of this book has crafted an accessible introduction that demystifies machine learning without sacrificing accuracy or depth. By focusing on intuitive explanations, practical examples, and real-world applications, this guide bridges the gap between complex technical concepts and practical understanding. Whether you're a student considering a career in technology, a professional looking to understand how AI might impact your industry, or simply a curious individual wanting to understand the algorithms that increasingly shape our world, this book provides the foundation you need.

Ned discovers a hard truth about his past but will it also endanger the future of the universe? After reconnecting with an old acquaintance, Hank’s AI companion is on the hunt for more information and it just might bring them closer than ever to Twain. But the old Enemy AI has a few tricks up his sleeve. And while they pursue the villain, the crew also find themselves in the crosshairs. Having angered a shadowy sect, the hunters become the hunted.

Hugh Howey is known for crafting riveting and immersive tales of boundless imagination. Now comes Machine Learning, an impressive collection of Howey's science fiction and fantasy short fiction, including three stories set in the world of Wool, two never-before-published tales written exclusively for this volume, and 15 additional stories collected here for the first time. These stories explore everything from artificial intelligence to parallel universes to video games, and each story is accompanied by an author's note.

Machine Learning for Absolute Beginners Third Edition has been written and designed for absolute beginners. This means plain-English explanations and no coding experience required.

Machine learning systems are both complex and unique. Complex because they consist of many different components and involve many different stakeholders. Unique because they're data dependent, with data varying wildly from one use case to the next. In this book, you'll learn a holistic approach to designing ML systems that are reliable, scalable, maintainable, and adaptive to changing environments and business requirements. Author Chip Huyen, cofounder of Claypot AI, considers each design decision in the context of how it can help your system as a whole achieve its objectives.

Chatbots such as the infamous ChatGPT, robotic warehouses, computerized call centres and patient diagnosis. These are just a few of the areas where Artificial Intelligence (AI) and Machine Learning are being used to boost revenues, cut costs, save lives and improve customer experiences. As a result, organizations that understand these tools and know how to use them are benefiting at the expense of their rivals. This book cuts through the hype and technical jargon that one often finds when talking about AI and Machine Learning. It delivers a short, concise and non-technical guide for ...

We are living through a revolution in machine learning-powered AI that shows no signs of slowing down. This technology is based on relatively simple mathematical ideas, some of which go back centuries, including linear algebra and calculus, the stuff of seventeenth- and eighteenth-century mathematics. It took the birth and advancement of computer science and the kindling of 1990s computer chips designed for video games to ignite the explosion of AI that we see today. In this enlightening book, Anil Ananthaswamy explains the fundamental math behind machine learning.

Becoming a Data Head is a complete guide for data science in the workplace: covering everything from the personalities you’ll work with to the math behind the algorithms. The authors have spent years in data trenches and sought to create a fun, approachable, and eminently bingeable book. Anyone can become a Data Head—an active participant in data science, statistics, and machine learning. Whether you're a business professional, engineer, executive, or aspiring data scientist, this book is for you.

Are you intrigued by the world of AI and data engineering? Do you find yourself captivated by the potential of these technologies to transform businesses and industries? If so, Data Engineering and AI for Beginners is the introductory guide you've been searching for. In today’s fast evolving digital landscape where data is lifeblood, those who harness its flow hold the keys to game-changing insights. This book addresses the very challenges and questions that have been on your mind: What is Data Engineering? How Does AI Fit into the Picture? Is This for Me, a Beginner? What Tools and ...

In this audiobook, machine learning expert Ethem Alpaydin offers a concise overview of the subject for the general listener, describing its evolution, explaining important learning algorithms, and presenting example applications. Alpaydin offers an account of how digital technology advanced from number-crunching mainframes to mobile devices, putting today's machine learning boom in context.

Machine learning (ML) is changing virtually every aspect of our lives. Today ML algorithms accomplish tasks that until recently only expert humans could perform. As it relates to finance, this is the most exciting time to adopt a disruptive technology that will transform how everyone invests for generations. The book addresses real-life problems faced by practitioners on a daily basis and explains scientifically sound solutions using math, supported by code and examples.

Through a recent series of breakthroughs, deep learning has boosted the entire field of machine learning. Now, even programmers who know close to nothing about this technology can use simple, efficient tools to implement programs capable of learning from data. This bestselling book uses concrete examples, minimal theory, and production-ready Python frameworks (Scikit-Learn, Keras, and TensorFlow) to help you gain an intuitive understanding of the concepts and tools for building intelligent systems.

If you need a go-to guide with numerous examples and coded programs, Python Machine Learning will be the answer. If you want to train your own models and enhance them to achieve your demand, Python Machine Learning is the exact tool. Do you want to train the machines and model to carry out complex jobs with accurate date and predictions in a more efficient way? Do you want to have a quick start in the right direction to enter into the Python world?

If you're looking to make a career move from programmer to AI specialist, this is the ideal place to start. Based on Laurence Moroney's extremely successful AI courses, this introductory book provides a hands-on, code-first approach to help you build confidence while you learn key topics.

Today's "machine-learning" systems, trained by data, are so effective that we've invited them to see and hear for us - and to make decisions on our behalf. But alarm bells are ringing. Systems cull résumés until, years later, we discover that they have inherent gender biases. Algorithms decide bail and parole - and appear to assess black and white defendants differently. We can no longer assume that our mortgage application, or even our medical tests, will be seen by human eyes. And autonomous vehicles on our streets can injure or kill.

As tech products become more prevalent today, the demand for machine learning professionals continues to grow. But the responsibilities and skill sets required of ML professionals still vary drastically from company to company, making the interview process difficult to predict. In this guide, data science leader Susan Shu Chang shows you how to tackle the ML hiring process. She'll take you through the highly selective recruitment process by sharing hard-won lessons she learned along the way.

The deep-learning revolution has brought us driverless cars, the greatly improved Google Translate, fluent conversations with Siri and Alexa, and enormous profits from automated trading on the New York Stock Exchange. Deep-learning networks can play poker better than professional poker players and defeat a world champion at Go. In this book, Terry Sejnowski explains how deep learning went from being an arcane academic field to a disruptive technology in the information economy.

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 analysis, each new project builds on what you’ve learned in previous chapters. You’ll build a portfolio of business-relevant machine learning projects that hiring managers will be excited to see.

Artificial Intelligence & Machine Learning By Morgan Steele Master Modern AI with Real-World Applications, Hands-On Projects, and Clear Explanations Unlock the power of AI and machine learning with this practical guide designed for developers, analysts, and tech professionals at every level. Whether you're building intelligent systems, exploring generative AI, or preparing for a career in data science, this book provides the tools and knowledge to get you there. Inside, you'll learn: Core concepts of AI and how machines learn Supervised, unsupervised, and reinforcement learning explained ...

Unlock the Secrets of AI Deep Learning and Neural Networks: Empower Your Future in Minutes a Day! Ready to dive into the world of artificial intelligence, but don’t know where to start? Whether you're a student, developer, or curious learner, this book takes you on a journey to master deep learning concepts, demystify neural networks, and transform your skills into real-world impact—all at your own pace.