Machine Learning Engineering

"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 ...

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.

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.

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 ...

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.

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.

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.

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 ...

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.

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.

Running your own business means no two days ever look quite the same. One moment you’re replying to client emails, the next you’re brainstorming your next big project, and somewhere in between, you’re wearing a whole wardrobe of hats you never planned to own. When your to-do list seems to grow faster than you can check things off, it’s natural to wish for a better way to manage the chaos, without losing the personal touch that makes your business yours. That’s where this book comes in. Whether you’re feeling stuck at a crossroads, craving a little more order in your workday, or ...

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?

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

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.

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.

This book serves as a comprehensive guide for individuals preparing for interviews in the field of prompt systems. It covers various roles within the prompt system domain, providing insights and practical information for each. Readers will explore the responsibilities of a prompt system architect, who designs and oversees the architecture, ensuring scalability and reliability. The book also delves into prompt system development, discussing coding, software optimization, module integration, and the implementation of prompt algorithms. Additionally, readers will gain an understanding of the ...

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.

The ultimate guide of how-to templates with real-world examples that demystify the art and science of AI prompt writing, offering clear frameworks, proven templates, and step-by-step instructions. This empowering guide reveals the exact formulas behind successful prompts with structured templates, troubleshooting guides, and practical exercises. Develop the critical thinking skills needed to achieve consistent, high-quality AI outputs.

Dear writers, it’s been a light year since ChatGPT introduced artificial intelligence into the world of writing. And oh, what a year it has been. By now, you’ve probably tried using AI to brainstorm premises, write marketing copy, develop characters, and build worlds. * * * Do you wish to do more? • Are you curious about what you can do beyond using ChatGPT? • Ready to learn how to customize AI to your own writing? • Wondering how to keep up with the pace of AI? Fear not. I’m Rachelle Ayala, a USA Today Bestselling author and AI trailblazer. I’m here to equip you with the ...