If you're looking to make a career move from programmer to AI specialist, this is the ideal place to start. Based on Laurence Moroney's extremely successful AI courses, this introductory book provides a hands-on, code-first approach to help you build confidence while you learn key topics.

Curious about AI, but unsure how it works? Want to tap into the lucrative potential of this rapidly advancing technology? Unlock the immense potential of AI with this transformative book! Welcome to Fundamentals of Artificial Intelligence & Large Language Models, the second in a series of books crafted to help you join a movement toward a more financially fruitful future.

Data engineering has grown rapidly in the past decade, leaving many software engineers, data scientists, and analysts looking for a comprehensive view of this practice. With this practical book, you'll learn how to plan and build systems to serve the needs of your organization and customers by evaluating the best technologies available through the framework of the data engineering lifecycle.

In Large Language Model-Based Solutions: How to Deliver Value with Cost-Effective Generative AI Applications, Principal Data Scientist at Amazon Web Services, Shreyas Subramanian, delivers a practical guide for developers and data scientists who wish to build and deploy cost-effective large language model (LLM)-based solutions. In the book, you'll find coverage of a wide range of key topics, including how to select a model, pre- and post-processing of data, prompt engineering, and instruction fine-tuning.

From script-free customer service chatbots to fully independent agents operating seamlessly in the background, AI-powered assistants represent a breakthrough in machine intelligence. In AI Agents in Action, you'll master a proven framework for developing practical agents that handle real-world business and personal tasks.

There are no easy decisions in software architecture. Instead, there are many hard parts—difficult problems or issues with no best practices—that force you to choose among various compromises. With this book, you'll learn how to think critically about the trade-offs involved with distributed architectures. Architecture veterans and practicing consultants Neal Ford, Mark Richards, Pramod Sadalage, and Zhamak Dehghani discuss strategies for choosing an appropriate architecture.

This book is for programmers who want to learn JavaScript and for web developers who want to take their understanding and mastery to the next level. It begins by explaining the JavaScript language itself, in detail, from the bottom up. It then builds on that foundation to cover the web platform and Node.js.

Recent breakthroughs in AI have not only increased demand for AI products, they've also lowered the barriers to entry for those who want to build AI products. The model-as-a-service approach has transformed AI from an esoteric discipline into a powerful development tool that anyone can use. Everyone, including those with minimal or no prior AI experience, can now leverage AI models to build applications. In this book, author Chip Huyen discusses AI engineering: the process of building applications with readily available foundation models.

In this book, author Will Larson shows you ways to obtain your first executive job and quickly ramp up to meet the challenges you may not have encountered in non-executive roles: measuring engineering for both engineers and the CEO, company-scoped headcount planning, communicating successfully across a growing organization, and figuring out what people actually mean when they keep asking for a "technology strategy."

MULTIPLE TIME AMAZON BESTSELLER Version 4 - Completely revised and updated for the new Cisco exam: 200-301 CCNA Implementing and Administering Cisco Solutions (CCNA) Since 2009, this book has been used by thousands of Cisco students to study for their CCNA exams. Written by a CCNP and three CCIEs, it's all you need to pass the new style exam. FREE SUPPORT The book is supported for free so just come over and register your copy to get free access to over $400 worth of videos, exams, cram guides - in60days.com/free/ccnain60days/ ABOUT THE BOOK Do any of the following problems sound familiar to...

Easy to understand and engaging, this updated edition of Introducing Python is ideal for beginning programmers as well as those new to the language. Author Bill Lubanovic takes you from the basics to more involved and varied topics, mixing tutorials with cookbook-style code recipes to explain concepts in Python 3. End-of-chapter exercises help you practice what you've learned.

When it comes to choosing, using, and maintaining a database, understanding its internals is essential. But with so many distributed databases and tools available today, it's often difficult to understand what each one offers. With this practical guide, Alex Petrov guides developers through the concepts behind modern database and storage engine internals.

Becoming a Data Head is a complete guide for data science in the workplace: covering everything from the personalities you’ll work with to the math behind the algorithms. The authors have spent years in data trenches and sought to create a fun, approachable, and eminently bingeable book. Anyone can become a Data Head—an active participant in data science, statistics, and machine learning. Whether you're a business professional, engineer, executive, or aspiring data scientist, this book is for you.

This audiobook is a summary of the advice I’ve given to software engineers over the years–and then some more. This audiobook follows the structure of a “typical” career path for a software engineer, from starting out as a fresh-faced software developer, through being a role model senior/lead, all the way to the staff/principle/distinguished level. It summarizes what I’ve learned as a developer and how I’ve approached coaching engineers at different stages of their careers.

In The Optimist, the Wall Street Journal reporter Keach Hagey presents the most detailed account yet of Altman’s rise, from his precocious childhood in St. Louis to his first, failed startup experience; his time as legendary entrepreneur Paul Graham’s protégé and successor as head of Y Combinator, the start-up accelerator where Altman became the premier power broker in Silicon Valley; the founding of OpenAI and his recruitment of a small yet superior team; and his struggle to keep his company at the cutting edge while fending off determined rivals, including Elon Musk.

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.

Deep Learning with Python (Second Edition) introduces the field of deep learning using Python and the powerful Keras library. In this revised and expanded new edition, Keras creator François Chollet offers insights for both novice and experienced machine learning practitioners. As you move through this book, you’ll build your understanding through intuitive explanations and clear examples. You’ll quickly pick up the skills you need to start developing deep learning applications.

Recent breakthroughs in AI have not only increased demand for AI products, they've also lowered the barriers to entry for those who want to build AI products. The model-as-a-service approach has transformed AI from an esoteric discipline into a powerful development tool that anyone can use. Everyone, including those with minimal or no prior AI experience, can now leverage AI models to build applications. In this book, author Chip Huyen discusses AI engineering: the process of building applications with readily available foundation models.

AI has acquired startling new language capabilities in just the past few years. Driven by rapid advances in deep learning, language AI systems are able to write and understand text better than ever before. This trend is enabling new features, products, and entire industries. With this book, listeners will learn practical tools and concepts they need to use these capabilities today.

From script-free customer service chatbots to fully independent agents operating seamlessly in the background, AI-powered assistants represent a breakthrough in machine intelligence. In AI Agents in Action, you'll master a proven framework for developing practical agents that handle real-world business and personal tasks.

Natural Language Processing in Action is your guide to building machines that can read and interpret human language. In it, you'll use readily available Python packages to capture the meaning in text and react accordingly. The book expands traditional NLP approaches to include neural networks, modern deep learning algorithms, and generative techniques as you tackle real-world problems like extracting dates and names, composing text, and answering free-form questions.

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.

As a software engineer, you’ll encounter countless programming challenges that initially seem confusing, difficult, or even impossible. Don’t despair! Many of these “new” problems already have well-established solutions. Advanced Algorithms and Data Structures teaches you powerful approaches to a wide range of tricky coding challenges that you can adapt and apply to your own applications. Providing a balanced blend of classic, advanced, and new algorithms, this practical guide upgrades your programming toolbox with new perspectives and hands-on techniques.

There are countless ways to put deep learning to good use: improved medical imaging, credit card fraud detection, long range weather forecasting. PyTorch puts these superpowers in your hands, providing a comfortable Python experience that gets you started quickly and then grows with you as you - and your deep-learning skills - become more sophisticated.

Large language models (LLMs) are not just shaping the trajectory of AI, they're also unveiling a new era of security challenges. This practical book takes you straight to the heart of these threats. Author Steve Wilson, chief product officer at Exabeam, focuses exclusively on LLMs, eschewing generalized AI security to delve into the unique characteristics and vulnerabilities inherent in these models.

When it comes to choosing, using, and maintaining a database, understanding its internals is essential. But with so many distributed databases and tools available today, it's often difficult to understand what each one offers. With this practical guide, Alex Petrov guides developers through the concepts behind modern database and storage engine internals.

Curious about AI, but unsure how it works? Want to tap into the lucrative potential of this rapidly advancing technology? Unlock the immense potential of AI with this transformative book! Welcome to Fundamentals of Artificial Intelligence & Large Language Models, the second in a series of books crafted to help you join a movement toward a more financially fruitful future.

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.

Data engineering has grown rapidly in the past decade, leaving many software engineers, data scientists, and analysts looking for a comprehensive view of this practice. With this practical book, you'll learn how to plan and build systems to serve the needs of your organization and customers by evaluating the best technologies available through the framework of the data engineering lifecycle.

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.