Computer Language

Dave Thomas and Andy Hunt wrote the first edition of this influential book in 1999 to help their clients create better software and rediscover the joy of coding. These lessons have helped a generation of programmers examine the very essence of software development. Now, 20 years later, this new edition re-examines what it means to be a modern programmer. Topics range from personal responsibility and career development to architectural techniques for keeping your code flexible and easy to adapt and reuse.

When you need a language model to respond accurately and quickly about a specific field of knowledge, the sprawling capacity of an LLM may hurt more than it helps. This book teaches you to build generative AI models optimized for specific fields.

The bestselling book on Python deep learning, now covering generative AI, Keras 3, PyTorch, and JAX! Deep Learning with Python (Third Edition) puts the power of deep learning in your hands. This new edition includes the latest Keras and TensorFlow features, generative AI models, and added coverage of PyTorch and JAX. Learn directly from the creator of Keras and step confidently into the world of deep learning with Python.

Are you aware that C is one of the most popular and commonly-used programming languages today? Did you know many expert developers have started learning C in order to become knowledgeable in computer programming? Do you want a simple way to understand step-by-step actions to learning C programming, while skipping all the technical jargon so many learners fear in programming? If you are having doubts about learning the language, do not! C is actually easy to learn. Compared to C++, C is much simpler!

In Build a Large Language Model (from Scratch) bestselling author Sebastian Raschka guides you step by step through creating your own LLM. Each stage is explained with clear text, diagrams, and examples. You’ll go from the initial design and creation, to pretraining on a general corpus, and on to fine-tuning for specific tasks.

If you want to learn how to program in Python, but don't know where to start read on. Knowing where to start when learning a new skill can be a challenge, especially when the topic seems so vast. There can be so much information available that you can't even decide where to start. Or worse, you start down the path of learning and quickly discover too many concepts, commands, and nuances that aren't explained.

The world of computers is growing at an unrecordable rate every day. Computers are the most influential tools in our lives. They are our present and future. Most users see a computer at the front and use the graphical user interfaces. The first time I used a computer, it intrigued me to know how these interfaces work. In this book, you will learn the same way I did.

Looking at the emergence of generative AI, Language Machines presents a new theory of meaning in language and computation, arguing that humanistic scholarship misconstrues how large language models (LLMs) function. Seeing LLMs as a convergence of computation and language, Leif Weatherby contends that AI does not simulate cognition, as widely believed, but rather creates culture.

Unlock the potential of Generative AI with this Large Language Model production-ready playbook for seamless deployment, optimization, and scaling. This hands-on guide takes you beyond theory, offering expert strategies for integrating LLMs into real-world applications using retrieval-augmented generation (RAG), vector databases, PEFT, LoRA, and scalable inference architectures. Whether you're an ML engineer, data scientist, or MLOps practitioner, you’ll gain the technical know-how to operationalize LLMs efficiently, reduce compute costs, and ensure rock-solid reliability in production.

Becoming a solutions architect requires a hands-on approach, and this edition of the Solutions Architect's Handbook brings exactly that. This audiobook will teach you how to create robust, scalable, and fault-tolerant solutions and next-generation architecture designs in a cloud environment. It will also help you build effective product strategies for your business and implement them from start to finish.

This program includes an introduction read by the author. No recent scientific enterprise has proved as alluring, terrifying, and filled with extravagant promise and frustrating setbacks as artificial intelligence. The award-winning author Melanie Mitchell, a leading computer scientist, now...

Technical knowledge alone isn't enough - increase your software development income by leveling up your soft skills Early in his software developer career, John Sonmez discovered that technical knowledge alone isn't enough to break through to the next income level - developers need "soft skills" like the ability to learn new technologies just in time, communicate clearly with management and consulting clients, negotiate a fair hourly rate, and unite teammates and coworkers in working toward a common goal.

NEW YORK TIMES BESTSELLER From linguist Adam Aleksic, known as @etymologynerd on social media, comes a captivating exploration of how internet algorithms are transforming language and communication in unprecedented ways. “Packed with fascinating facts, of-the-moment observations, and a...

Are you aware that C programming is one of the most popular and commonly used programming languages today and that your children may even be learning it in their schools? And did you know that many expert developers began their careers by learning C programming? If you're looking for a shortcut to go from a basic to an expert programmer, this is the book for you! And no worries, all technical jargon is removed, making it easier for you to understand.

To score a job in data science, machine learning, computer graphics, and cryptography, you need to bring strong math skills to the party. Math for Programmers teaches the math you need for these hot careers, concentrating on what you need to know as a developer. Filled with lots of helpful graphics and more than 200 exercises and mini-projects, this book unlocks the door to interesting - and lucrative! - careers in some of today’s hottest programming fields about the technology.

From the coauthor of Algorithms to Live By, an exploration of the quest to use mathematics to describe the ways we think, from its origins three hundred years ago to the ideas behind modern AI systems and the ways in which they still differ from human minds Everyone has a basic understanding of...

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.

This friendly guide teaches you how to apply common algorithms to the practical problems you face every day as a programmer. You'll start with sorting and searching and, as you build up your skills in thinking algorithmically, you'll tackle more complex concerns such as data compression and artificial intelligence. This accesible introduction is suitable for self-taught programmers, engineers, or anyone who wants to brush up on algorithms. Each carefully presented example includes helpful diagrams and fully annotated code samples in Python.

Microsoft project veteran Scott Berkun offers a collection of essays on field-tested philosophies and strategies for defining, leading, and managing projects. Each essay distills complex concepts and challenges into practical nuggets of useful advice, and the new edition now adds more value for leaders and managers of projects everywhere.  

Terrence Sejnowski offers a nuanced exploration of large language models (LLMs) like ChatGPT and what their future holds. How should we go about understanding LLMs? Do these language models truly understand what they are saying? Or is it possible that what appears to be intelligence in LLMs may be a mirror that merely reflects the intelligence of the interviewer? In this book, Sejnowski, a pioneer in computational approaches to understanding brain function, answers all our urgent questions about this astonishing new technology.