Science Machine Learning

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.

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.

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.

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.

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. 

A collection of shockingly prescient stories covering topics from aliens to AI, including some that have never before been seen, from the New York Times best-selling author of the Silo trilogy Hugh Howey is known for crafting riveting and immersive page-turners of boundless imagination, spawning...

Real-World Machine Learning will teach you the concepts and techniques you need to be a successful machine learning practitioner without overdosing you on abstract theory and complex mathematics. By working through immediately relevant examples in Python, you'll build skills in data acquisition and modeling, classification, and regression. You'll also explore the most important tasks like model validation, optimization, scalability, and real-time streaming. When you're done, you'll be ready to successfully build, deploy, and maintain your own powerful ML systems.

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.

Make learning painless, exciting, habitual, and self-motivating. Absorb info like a human sponge. We’ve never been taught how to learn, and that’s a shame. This book is the key to reversing all the misconceptions you have and making learning fun again.

Graph-Powered Machine Learning teaches to use graph-based algorithms and data organization strategies to develop superior machine learning applications. You’ll dive into the role of graphs in machine learning and big data platforms, and take an in-depth look at data source modeling, algorithm design, recommendations, and fraud detection. Explore end-to-end projects that illustrate architectures and help you optimize with best design practices.

The most human-friendly book on machine learning Somewhere buried in all the systems that drive artificial intelligence, you'll find machine learning―the process that allows technology to build knowledge based on data and patterns. Machine Learning For Dummies is an excellent starting point...

Discover valuable machine learning techniques you can understand and apply using just high school math. Grokking Machine Learning teaches you how to apply ML to your projects using only standard Python code and high school-level math. No specialist knowledge is required to tackle the hands-on exercises using Python and readily available machine learning tools. Packed with easy-to-follow Python-based exercises and mini-projects, this book sets you on the path to becoming a machine learning expert.

Need Machine clamors through the brain like an unruly marching band. Both caustic and thoughtful, these poems offer a topography of modern life writ large in twitchy, neon splendor, in a voice as sure as a surgeon and as trustworthy as a rumor. Honest, irreverent, and sharply indifferent, this audiobook will "hogtie you with awe."

If you need to learn how to use machine learning, big data, data science, and neural networks but you can’t (or there is no time to) study the complicated math and algorithms behind these technologies, then keep reading. All technologies related to artificial intelligence represent an incredible opportunity if you want to grow your business or if you are searching for a new job, but it’s not very easy to understand how they work.

Ever wondered how your favorite apps predict your preferences or how self-driving cars navigate the roads? Welcome to the world of Machine Learning, where these wonders come to life! "Introduction to Machine Learning" is your ticket to unraveling the mysteries of this groundbreaking technology without the need for a PhD!

The greatest tool is the hardest to use. Machine learning is the world's most important general-purpose technology—but it's notoriously difficult to launch. Outside Big Tech and a handful of other leading companies, machine learning initiatives routinely fail to deploy, never realizing value. What's missing? A specialized business practice suitable for wide adoption. In The AI Playbook, bestselling author Eric Siegel presents the gold-standard, six-step practice for ushering machine learning initiatives, aka predictive AI projects, from conception to deployment.

Unleash the power of Generative AI in less than 30 days. Turn tech curiosity into a practical skillset even if you're a beginner. Don't let your perception of what's difficult hold you back. This book is designed specifically with simplicity in mind, tailored for those who may be stepping into the world of AI for the first time. It is packed with interactive, up-to-date exercises and real-world applications, that will guide you every step of the way, ensuring that you stay connected to the most relevant and useful topics in AI.

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.