Machine Learning Systems

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.

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.

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.

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.

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.

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.

To score a job in data science, machine learning, computer graphics, and cryptography, you need to bring strong math skills to the party. Math for Programmers teaches the math you need for these hot careers, concentrating on what you need to know as a developer. Filled with lots of helpful graphics and more than 200 exercises and mini-projects, this book unlocks the door to interesting - and lucrative! - careers in some of today’s hottest programming fields about the technology.

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.

Deep learning is rapidly gaining momentum in the world of finance and trading. But for many professional traders, this sophisticated field has a reputation for being complex and difficult. This hands-on guide teaches you how to develop a deep learning trading model from scratch using Python, and it also helps you create and backtest trading algorithms based on machine learning and reinforcement learning.

This audiobook teaches you how to build an intelligent system from end to end and leverage machine learning in practice. You will understand how to apply your existing skills in software engineering, data science, machine learning, management, and program management to produce working systems.

Machine learning and deep learning are changing technology as we know it. Critical infrastructure decisions are now driven by fine-tuned algorithms trained with huge data sets. In this guide, you're going to be handed all the information and tools you need to transform data into powerful insights.

In Not with a Bug, But with a Sticker: Attacks on Machine Learning Systems and What to Do About Them, a team of distinguished adversarial machine learning researchers deliver a riveting account of the most significant risk to currently deployed artificial intelligence systems: cybersecurity threats. The authors take you on a sweeping tour—from inside secretive government organizations to academic workshops at ski chalets to Google's cafeteria—recounting how major AI systems remain vulnerable to the exploits of bad actors of all stripes.

Are you confused about what all the rage behind artificial intelligence is and would like to learn more? This audiobook covers everything from machine learning to robotics and the internet of things. You can use it as a nifty guidebook whenever you come across news headlines that talk about some new advancement in AI by Google or Facebook. By the time you finish listening, you will be aware of what artificial neural networks are, how gradient descent and back propagation work, and what deep learning is.

Machine learning is everywhere. It is time for you to start learning what machine learning is all about, and you can do that with this book. Discover what neural networks are, about python and machine learning, examples of machine learning, how machine learning is beneficial to you, and so much more.

The aim of this book has been to provide students, educators, and administrators alike with valuable insights into the disruptive, yet beneficial, transformation which will occur in the global education system during the next three to five years and beyond. Although these trends will not happen immediately, their impact will be far-reaching and global in nature.

If you're looking to make the most of artificial intelligence and blockchain technology for your business, this audiobook is for you. Artificial intelligence and blockchain are the tech of the future. But if you're not already working in the field or studying their depths, it can be difficult to find information in layman's terms. As a business owner, especially a small business owner, we are always looking at ways to improve the efficiency of our business: outsource, automate, scale, marketing.... AI and blockchain technology could revolutionize the way business is done.

¿Está usted confundido acerca del furor que existe detrás de la inteligencia artificial y le gustaría aprender más? Este audiolibro lo abarca todo, desde el aprendizaje automático hasta la robótica y el Internet de las cosas. Usted puede usarlo como una guía útil cuando se encuentre con titulares de noticias que hablan de un nuevo avance en la inteligencia artificial por parte de Google o Facebook. Será consciente de lo que son las redes neuronales artificiales, cómo funcionan el descenso de gradiente y la propagación hacia atrás, y qué es el aprendizaje profundo.