Machine Learning Engineering

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. 

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.

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.

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.

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 powerful applications of AI have already transformed our daily lives. Virtual personal and home assistants (like Siri in Apple Pods and Alexa in Amazon Echo) have become everyday use products. Artificial intelligence and machine learning are closely related. They have become an important part of scientific study. It involves the study of statistical models and algorithms and the systems used for task performance. Our aim with this audiobook is to provide you a 360 degree view of the fundamentals and importance of machine learning technology for the beginners’ level.

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 ...

Embrace the future and unlock the potential of AI-driven language models to reshape your business and achieve unprecedented growth and success with this groundbreaking book, The GPT-4 MILLIONAIRE: FUTURE OF BUSINESS Featuring Microsoft 365 Copilot: How to Leverage AI Language Models to Grow Your Company and How AI-driven Language Models Will Revolutionize the Way We Work. Discover the transformative power of GPT-4, a state-of-the-art AI-driven language model, and its integration with Microsoft 365 Copilot, as we explore the vast array of opportunities presented by these cutting-edge ...

It has never been easier for organizations to gather, store, and process data. Use of data science is driven by the rise of big data and social media, the development of high-performance computing, and the emergence of such powerful methods for data analysis and modeling as deep learning. Data science encompasses a set of principles, problem definitions, algorithms, and processes for extracting non-obvious and useful patterns from large datasets.

This painstakingly compiled manuscript unravels the rudiments and generality of machine learning. It is total and all-encompassing with accurate and concise principles of machine learning.  

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.

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.

To most of us, it seems like recent developments in artificial intelligence emerged out of nowhere to pose unprecedented threats to humankind. But to Dr. Joy Buolamwini, who has been at the forefront of AI research, this moment has been a long time in the making.

Artificial intelligence has become an inherent part of our everyday life. This book empowers you with the tools to discover and learn AI systems and languages to understand how they work and benefit today’s world, to let go of the fear that AI will outsmart the human race. This book is a practical guide for all who want to understand how AI is changing the world they live in today. Are you ready to discover the AI secrets that will give you an upper hand on this rapidly developing industry?

Do you know how to build a machine learning algorithm in Python? Have you learned how to build a neural network in Python? If you have listened to the first three audiobooks in the series, you will know how to do both those things. If you want to learn more about the concepts related to machine learning and some subjects and concepts that are linked to machine learning, you have come to the right place.

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.

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.

This book on machine learning will explain the concepts, methods, and history behind machine learning. Learn what it is, its importance, history, and much more.