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...

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.

A decade ago, developers built information-sharing software by writing a lot of custom code in a single code base, then adding layers of caching. Now we build information systems: interdependent software and services, data platforms, and event streams. Many of our software-to-systems initiatives fail, though, and when they do, we double down on traditional linear approaches. But linear thinking cannot resolve systems challenges. We need to shift to systems thinking.

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. 

Featured by Tableau as the first of "7 Books About Machine Learning for Beginners." Ready to spin up a virtual GPU instance and smash through petabytes of data? Want to add "Machine Learning" to your LinkedIn profile? Well, hold on there.... Before you embark on your journey, there are some...

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.

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.

Are you a machine-learning enthusiast looking for a practical day-to-day application? Or are you just trying to incorporate machine-learning software in your trading decisions? This audiobook is your answer.

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.

A compelling new set of interviews on our changing and turbulent times with Noam Chomsky, one of the world's foremost thinkers In this collection of conversations, conducted from 2010 to 2012, Noam Chomsky explores the most immediate and urgent concerns: the future of democracy in the Arab world...

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.

Ontdek hoe je efficiënte AI-systemen ontwerpt die rechtvaardigheid, autonomie en veiligheid in de praktijk borgen. Voor professionals die tijdens hun werk worstelen met technologische ethiek, biedt deze nuchtere, inzichtelijke luisterervaring directe houvast. Maak de vertaalslag van abstracte...

Bloomsbury presents Governing the Machine by Ray Eitel-Porter, Paul Dongha and Miriam Vogel, read by Miriam Vogel and Oliver Hembrough ‘Responsible AI isn’t just a technical challenge – it’s a leadership imperative. This book offers essential guidance for anyone navigating the promise of...

Demystify artificial intelligence and machine learning to future-proof your career, all without writing a line of code. Whether you are listening on your morning commute or upskilling for a promotion, this accessible guide transforms intimidating tech jargon into clear, actionable knowledge...

Transform machine learning theory into reliable, production-ready software products that drive real business value. Whether you are upskilling during your morning commute or transitioning into a specialized technical role, this practical guide cuts through the hype. You will gain the focused...

Are you ready to join the revolution that’s transforming sports betting? How to Start Sports Betting with AI is the ultimate step-by-step guide that bridges the gap between advanced data science and practical betting strategies—designed for beginners and experienced bettors alike.

With the rise of autonomous agents, the question is no longer "How do we build agents?" but rather, "How do we manage an entire ecosystem of them?" This book explores the next frontier of this technology, where interconnected agents collaborate, transact, and fulfill tasks autonomously. Building...

Transform predictive modeling into powerful decision-making with practical causal inference tools for real-world AI. Whether commuting to the office or deep in focused learning, this guide bridges the gap between correlation and true causation. Stop relying on naive analyses that fail when...

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.