Science Machine Learning

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.

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.

Ned discovers a hard truth about his past but will it also endanger the future of the universe? After reconnecting with an old acquaintance, Hank’s AI companion is on the hunt for more information and it just might bring them closer than ever to Twain. But the old Enemy AI has a few tricks up his sleeve. And while they pursue the villain, the crew also find themselves in the crosshairs. Having angered a shadowy sect, the hunters become the hunted.

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.

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.

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.

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.

Chatbots such as the infamous ChatGPT, robotic warehouses, computerized call centres and patient diagnosis. These are just a few of the areas where Artificial Intelligence (AI) and Machine Learning are being used to boost revenues, cut costs, save lives and improve customer experiences. As a result, organizations that understand these tools and know how to use them are benefiting at the expense of their rivals. This book cuts through the hype and technical jargon that one often finds when talking about AI and Machine Learning. It delivers a short, concise and non-technical guide for ...

Unlock the Secrets of AI Deep Learning and Neural Networks: Empower Your Future in Minutes a Day! Ready to dive into the world of artificial intelligence, but don’t know where to start? Whether you're a student, developer, or curious learner, this book takes you on a journey to master deep learning concepts, demystify neural networks, and transform your skills into real-world impact—all at your own pace.

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?

*Start your Data Science career using Python today!* Want to begin a new lucrative career as a Data Scientist? Learn to solve real world problems using Artificial Intelligence and Machine Learning skills – with step-by-step instructions and downloadable code samples! Are you interested in becoming a Data Scientist but overwhelmed by the complexity and don’t know where to start? Then let this breezy and fun little book on Python and machine learning models make you a data scientist in 7 days! This book is for beginners who would like to master predictive analytics and obtain a job in ...

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 bundle includes two audiobooks: Neural Networks and Deep Learning! You will understand the basics of what neural networks are, how they work, and the many tasks you can apply them to. This audiobook will also explain to you in simple layman’s terms the basic foundation and concept of deep learning and how it works.

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.

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.

The deep-learning revolution has brought us driverless cars, the greatly improved Google Translate, fluent conversations with Siri and Alexa, and enormous profits from automated trading on the New York Stock Exchange. Deep-learning networks can play poker better than professional poker players and defeat a world champion at Go. In this book, Terry Sejnowski explains how deep learning went from being an arcane academic field to a disruptive technology in the information economy.

The Neuroscience of Learning: How Brain Science and AI Can Elevate Your Learning What if you could learn faster, retain information more effectively, and unlock hidden potential within your mind? In The Neuroscience of Learning, discover the groundbreaking science behind how we learn and the practical applications that can make us all better learners. Blending leading-edge neuroscience with everyday insights, this book offers a transmutative look at how our brains function during learning, the influence of emotions and motivation, and the remarkable ways our brains’ neuroplasticity allows...

In this audiobook, you'll get a clear overview of artificial intelligence technology, the common misconceptions surrounding it, and a fascinating look at its applications in everything from self-driving cars and drones to its contributions in the medical field.

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.