Machine Learning Engineering

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.

Artificial Intelligence in Practice is a fascinating look into how companies use AI and machine learning to solve problems. Presenting 50 case studies of actual situations, this book demonstrates practical applications to issues faced by businesses around the globe. The rapidly evolving field of artificial intelligence has expanded beyond research labs and computer science departments and made its way into the mainstream business environment. Artificial intelligence and machine learning are cited as the most important modern business trends to drive success.

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.

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 for Engineers" is a foundational textbook meticulously crafted to introduce B.Tech and M.Tech engineering students to the principles and practices of Machine Learning (ML). This book serves as a bridge, connecting the theoretical underpinnings of ML algorithms with their practical application in solving complex engineering problems. Recognizing that the engineers of tomorrow must be adept at leveraging data, this book demystifies ML, making it accessible, intuitive, and directly relevant to their discipline. Key Features: 1. NEP 2020 and AICTE Compliant: The structure and ...

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 ...

We are living through a revolution in artificial intelligence that is not slowing down. This major shift is based on simple mathematics, some of which goes back centuries: linear algebra and calculus, the stuff of eighteenth-century mathematics. Indeed by the mid-1850s, a lot of the groundwork was all done. In this enlightening book, Anil Ananthaswamy explains the fundamental maths behind AI, which suggests that the basics of natural and artificial intelligence might follow the same mathematical rules.

Practical Data & AI for Engineers Applied Machine Learning, Data Pipelines, and AI Integration in Engineering Projects In today’s engineering world, data and artificial intelligence are no longer optional — they are essential. Practical Data & AI for Engineers bridges the gap between traditional engineering practice and the new era of intelligent automation, predictive analytics, and digital twins. This hands-on guide provides a real-world, engineering-focused introduction to applied machine learning, data management, and AI-driven solutions. It shows how engineers across disciplines ...

Author Martin Kleppmann helps you navigate the diverse data landscape by examining the pros and cons of various technologies for processing and storing data. Software keeps changing, but the fundamental principles remain the same. With this book, software engineers and architects will learn how to apply those ideas in practice, and how to make full use of data in modern applications.

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.

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.

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.

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.

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.

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 ...

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.

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?

The human brain is an extraordinary machine. Its ability to process information and adapt to circumstances by reprogramming itself is unparalleled and it remains the best source of inspiration for recent developments in artificial intelligence. In How We Learn, Stanislas Dehaene decodes the brain's biological mechanisms, delving into the neuronal, synaptic, and molecular processes taking place. He explains why youth is such a sensitive period, but assures us that our abilities continue into adulthood and that we can enhance our learning and memory at any age.

The Prompt Engineer: A Comprehensive Guide to Becoming Highly Effective" is a book aimed at individuals seeking to develop their prompt engineering skills and become highly effective prompt engineers. The book covers a wide range of topics, including an overview of prompt engineering, essential skills for prompt engineers, tools of the trade, designing effective prompts, implementation and deployment, and advanced topics in prompt engineering. In the first chapter, readers will gain an understanding of what prompt engineering is and its applications in modern businesses. Chapter two delves ...

Have you ever wondered how your robot vacuum avoids your coffee table or how a self-driving car knows when to stop at a red light? What about the robots that dance on stage, deliver meals, or even roam the dusty surface of Mars? These aren't just science fiction anymore—they're part of an increasingly real and evolving world: the world of robotics. Robots are everywhere, from household gadgets to space-faring explorers, from robotic pets to factory arms assembling your smartphone. We see them in the news, in our homes, in medicine, in classrooms, and on construction sites.