A hands-on guide for delivering products infused with artificial intelligence! Learn how AI can improve content creation, accelerate data analysis, and upgrade process automation.

The Art of AI Product Development teaches you how to successfully integrate AI into your software products. Written for product managers, team leads, and anyone responsible for the success of a software product or service, this practical book introduces Generative AI, AI-assisted data analytics, intelligent process automation, and more. You’ll love the examples from across many industries that illustrate the power and versatility of AI-powered solutions.

Inside The Art of AI Product Development you will learn vital skills for the effective use of AI, including:

• Identifying market and business opportunities for AI
• Evaluating AI technologies for products and features
• Effectively communicating with data scientists and ML engineers
• Designing user-friendly AI interfaces
• Best practices in AI ethics, governance, and risk management

AI-powered software introduces new opportunities and challenges for product managers. This one-of-a-kind book guides you from initial design conversations through development, deployment, and day-to-day management with techniques to make the process efficient, secure, and cost effective. You’ll learn to capitalize on AI’s full potential for your business with strategies that set you on the path to market leadership in your industry.

Just the Docker you need to know in 22 bite-sized lessons!

No matter what role you have in IT, you’re likely to touch Docker at some point.

Whether you’re deploying a pre-built application, creating a secure test environment, or packaging components in a microservices system, Docker provides a straightforward system for bundling all the pieces together in a safe, portable “container” you can drop wherever it’s needed. In this freshly-revised bestseller, Docker expert Elton Stoneman guides through using containers for cloud migration, microservices, and handling legacy systems–all in 22 short lessons you can complete on your lunch break.

In Learn Docker in a Month of Lunches, Second Edition you’ll learn everything you need to know about Docker, including how to:

• Run applications in Docker containers on Linux and Windows
• Package applications as Docker images and share them on registries
• Model and run distributed applications with Docker Compose
• Add instrumentation to containerized applications
• Build and deploy apps with Docker in a CI/CD process

Docker revolutionized the way engineers build software. By bundling an application together with all its dependencies in a portable “container” that can be deployed almost anywhere, Docker makes it possible to manage applications without creating custom infrastructures. Free, open source, and battle-tested, Docker has quickly become must-know technology for developers and administrators.

Start your microservices projects right! Choosing the best design patterns, tools, deployment strategies, and team structure will maximize innovation, agility, time to market, and reliability.

In Designing Microservices you will learn:

• Lightweight tools for responsibility mapping, DDD, and bounded contexts
• API strategies, including REST, event-driven, GraphQL, RPC, and hybrid API approaches
• Microservice UI design, including micro frontends, frontend for backend, chat and voice interfaces
• Managing transactions spanning multiple microservices
• A holistic view of the data in your system
• Securing, monitoring, and testing your microservices
• Refactoring to microservices with minimal downtime
• Avoiding antipatterns

In Designing Microservices you’ll learn an elegant approach to microservices architecture that’s based on the principles of loose coupling, high cohesion, and isolation. Created by award-winning microservices veteran S. Ramesh, this cutting-edge method has been proven and tested in high-stakes enterprise environments.

This practical and approachable book covers the design challenges you’re most likely to encounter, alongside patterns and components to solve each problem. You’ll even learn strategies for selecting and equipping teams for maximum productivity.

Learn to build financial software hands-on using generative AI tools like ChatGPT and Copilot.

The software used by banks, trading firms, and other financial services has special requirements at every level, from securing the UI to making sure backend services comply with a host of regulations. Software engineers with FinTech experience are highly valued, and generative AI tools can make you even more productive. Build Financial Software with Generative AI (From Scratch) shows you how to deliver full stack financial services software, including Agile practices, research, testing strategies, security, documentation, and more, using AI tools like ChatGPT and Copilot.

In Build Financial Software with Generative AI (From Scratch) you will:

• Explore the core concepts of FinTech
• Speed development with generative AI tools
• Develop and deploy containerized services
• Create and document APIs
• Effectively visualize your data

In Build Financial Software with Generative AI (From Scratch) you’ll build working software for processing Automated Clearing House (ACH) files, a cornerstone technology of banking that moves trillions of dollars every year. You’ll work with generative AI technology throughout the full stack application, including researching the tech for your application, spinning up a bare bone starting project, answering domain questions, clarifying functionality, and troubleshooting Along the way, you’ll learn what sets FinTech projects apart from normal web apps.

These small Go projects will build big Go skills! Learn hands-on as you build 11 engaging applications.

In Learn Go with Pocket-Sized Projects you’ll create 11 small applications and tools, including:

• A currency convertor application
• A health tracking app
• A load balancer for sharing jobs between workers in the Cloud
• An HTML template
• A microcontroller-based temperature monitor
• …and more!

Learn Go with Pocket-Sized Projects teaches you to write professional-level Go code by creating handy tools and fun apps. Each small, self-contained project introduces important practical skills, including ensuring that your code is thoroughly tested and documented! You’ll make architectural decisions for your projects and organize your code in a maintainable way. Everything you learn is easy to scale-up to full-size Go applications.

Discover how machine learning, deep learning, and generative AI have transformed the pharmaceutical pipeline as you get a hands-on introduction to building models with PyTorch.

Machine Learning for Drug Discovery introduces the machine learning and deep learning techniques that drive modern medical research. Each chapter explores a real-world example from the pharmaceutical industry, showing you hands-on how researchers investigate treatments for cancer, malaria, autoimmune diseases, and more.

In Machine Learning for Drug Discovery you will learn:

• Drug discovery and virtual screening
• Classic ML, deep learning, and LLMs for drug discovery
• UsingRDKit to analyze molecular data
• Creating drug discovery models with PyTorch
• Replicating cutting-edge drug development research

Machine learning has accelerated the process of drug discovery, shortening the timeline for developing new medicines from decades to years or months. In this practical guide, you’ll learn to create the kind of machine learning models that make these discoveries possible.

Automate and accelerate everyday IT tasks using generative AI!

Read this book, and you may never write another “after incident” report from scratch again! Generative AI for the IT Pro reveals how you can automate dozens of your daily IT tasks with generative AI—including writing email and reports, setting up a chatbot to field helpdesk requests, evaluating disaster recovery plans, and more.

In Generative AI for the IT Pro you’ll learn how to:

• Write effective prompts for common IT tasks
• Optimize report generation, document handling, and workplace communication
• Resolve IT conflicts and crises
• Acquire new skills and upgrade your resume
• AI for security engineering and systems administration

How many times have you lost an entire day sifting through logs to find a latency issue? AI can do it in seconds! Do you need to update your documentation? Mere moments for AI. Are you writing scripts, upgrading security, and evaluating network designs? AI can handle it—if you know how to use it.

In this hands-on guide, automation experts Brandon Abshire and Chrissy LeMaire show you how AI tools like ChatGPT have made their lives a million times easier, and how it can do the same for you.

Accelerate your mastery of data analytics with the power of ChatGPT.

Whether you're a data novice or an experienced pro looking to do more work, faster, Starting Data Analytics with Generative AI and Python is here to help simplify and speed up your data analysis! Written by a pair of world-class data scientists and an experienced risk manager, the book concentrates on the practical analytics tasks you'll do every day.

Inside Starting Data Analytics with Generative AI and Python you’ll learn how to:

• Write great prompts for ChatGPT
• Perform end-to-end descriptive analytics
• Set up an AI-friendly data analytics environment
• Evaluate the quality of your data
• Develop a strategic analysis plan
• Generate code to analyze non-text data
• Explore text data directly with ChatGPT
• Prepare reliable reports

In Starting Data Analytics with Generative AI and Python you’ll learn how to improve your coding efficiency, generate new analytical approaches, and fine-tune data pipelines—all assisted by AI tools like ChatGPT. For each step in the data process, you’ll discover how ChatGPT can implement data techniques from simple plain-English prompts. Plus, you’ll develop a vital intuition about the risks and errors that still come with these tools.

A developer-centric look at quantum computing.

Quantum computing opens a new realm of possibilities for developers working in complex research and business domains like industrial simulation, predictive modeling, drug discovery, and operations research. Building Quantum Software: A developer’s guide gives you the foundation you’ll need to build the software for the quantum age.

In Building Quantum Software: A developer’s guide you will learn about:

• Quantum search, probability estimation, and quantum counting
• A practical introduction to quantum algorithms
• Quantum states, gates, and circuits
• Running software on simulators and quantum hardware
• Classical simulations of quantum computations

Quantum computers are rapidly becoming a realistic alternative for complex research and business problems. Building Quantum Software: A developer’s guide lays out the math and programming techniques you’ll need to apply quantum solutions to real challenges like predictions based on massive data sets and intricate simulations. You will learn which quantum algorithms and patterns apply to different types of problems and how to build your first quantum applications.

Learn how large language models like GPT and Gemini work under the hood in plain English.

How Large Language Models Work translates years of expert research on Large Language Models into a readable, focused introduction to working with these amazing systems. It explains clearly how LLMs function, introduces the optimization techniques to fine-tune them, and shows how to create pipelines and processes to ensure your AI applications are efficient and error-free.

In How Large Language Models Work you will learn how to:

• Test and evaluate LLMs
• Use human feedback, supervised fine-tuning, and Retrieval augmented generation (RAG)
• Reducing the risk of bad outputs, high-stakes errors, and automation bias
• Human-computer interaction systems
• Combine LLMs with traditional ML

How Large Language Models Work is written by some of the best machine learning researchers at Booz Allen Hamilton, including researcher Stella Biderman, Director of AI/ML Research Drew Farris, and Director of Emerging AI Edward Raff. In clear and simple terms, these experts lay out the foundational concepts of LLMs, the technology’s opportunities and limitations, and best practices for incorporating AI into your organization.

See how an AI assistant can bring your ideas to life immediately!

Once, to be a programmer you had to write every line of code yourself.

Now tools like GitHub Copilot can instantly generate working programs based on your description in plain English. An instant bestseller, Learn AI-Assisted Python Programming has taught thousands of aspiring programmers how to write Python the easy way—with the help of AI. It’s perfect for beginners, or anyone who’s struggled with the steep learning curve of traditional programming.

In Learn AI-Assisted Python Programming, Second Edition you’ll learn how to:

• Write fun and useful Python applications—no programming experience required!
• Use the GitHub Copilot AI coding assistant to create Python programs
• Write prompts that tell Copilot exactly what to do
• Read Python code and understand what it does
• Test your programs to make sure they work the way you want them to
• Fix code with prompt engineering or human tweaks
• Apply Python creatively to help out on the job

AI moves fast, and so the new edition of Learn AI-Assisted Python Programming, Second Edition is fully updated to take advantage of the latest models and AI coding tools. Written by two esteemed computer science university professors, it teaches you everything you need to start programming Python in an AI-first world. You’ll learn skills you can use to create working apps for data analysis, automating tedious tasks, and even video games. Plus, in this new edition, you’ll find groundbreaking techniques for breaking down big software projects into smaller tasks AI can easily achieve.

Write, refine, organize, and optimize AI prompts that generate relevant and useful text and images!

Generative AI models such as ChatGPT, Stable Diffusion, and Gemini can produce amazingly “human-like” news articles, document summaries, images, computer code, and more—if you know how to write effective prompts.

This book will teach you the prompt design and authoring skills you need to get useful and relevant responses from AI models, along with advanced prompting techniques for Retrieval Augmented Generation (RAG), building autonomous agents, and data privacy.

Prompt Engineering in Practice teaches you how to:

• Design prompts that generate accurate and readable responses from LLMs
• Mitigate hallucinations in LLM output
• Domain-aware content generation using RAG
• How AI model design affects your prompts
• Evaluate, optimize, and organize your prompts

Prompt engineering is the discipline of writing instructions for AI models to generate relevant, accurate, and usable completions. Prompt Engineering in Practice shows you how to engineer prompts that ensure the outputs of LLMs and other generative AI models exactly match your requirements. You’ll learn how to structure your objectives, take advantage of contextual details, and even pick the right model for your task.