Results narrated by "Julie Brierley" in All categories

The system design interview is one of the hardest challenges you'll face in the software engineering hiring process. This practical book gives you the insights, the skills, and the hands-on practice you need to ace the toughest system design interview questions and land the job and salary you want.

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.

AI agent technology is changing fast! This totally revised Second Edition of "AI Agents in Action" by Micheal Lanham guides you through the latest breakthroughs in large language model (LLM)-powered autonomy, from the Model Context Protocol (MCP) to advanced multi-agent collaboration and deployment. Whether you're upgrading your customer service systems, creating a research assistant, or deploying a fleet of internal agents to automate enterprise tasks, this hands-on guide will help you build trustworthy agents that can handle high-stakes tasks.

Build intelligent LLM-powered applications with agentic workflows and tool-based agents. AI-powered applications are rapidly becoming the new normal. Personal productivity assistants, coding agents, smarter search, and automated reporting tools are popping up everywhere. The LangChain ecosystem, and standards like MCP are driving this new gold rush. This book helps you claim your spot.

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.

Grokking Algorithms, Second Edition teaches you important algorithms to speed up your programs, simplify your code, and solve common programming problems. Start with tasks like sorting and searching, then build your skills to tackle advanced problems like data compression and artificial intelligence.

Fully updated to ASP.NET 5.0, ASP.NET Core in Action, Second Edition is a hands-on primer to building cross-platform web applications with your C# and .NET skills. Even if you've never worked with ASP.NET, you'll start creating productive cross-platform web apps fast. And don’t worry about late-breaking changes to ASP.NET Core.

Grokking Artificial Intelligence Algorithms is a fully illustrated and interactive tutorial guide to the different approaches and algorithms that underpin AI. Written in simple language and with lots of visual references and hands-on examples, you'll learn the concepts, terminology, and theory you need to effectively incorporate AI algorithms into your applications. And to make sure you truly grok as you go, you'll use each algorithm in practice with creative coding exercises.

"Fabulous Adventures in Data Structures and Algorithms" invites you to step off the beaten path and explore interesting, unfamiliar, and even exotic algorithms that will challenge your perspective and elevate your code. Legendary language designer Eric Lippert guides you with a refreshing, conversational approach, providing beautifully practical examples that highlight the recurring patterns behind stubborn coding problems. You'll begin with a fresh look at foundational, thread-safe, and persistent immutable data structures.

"Reinforcement Learning from Human Feedback: LLM alignment and post-training" helps you understand how modern AI models can be adapted to better match the needs and expectations of their users. Rather than surveying the vast field of reinforcement learning, elite AI researcher Nathan Lambert concentrates exclusively on RLHF and its immediate importance to post-training generative AI models.

Regular Expression Puzzles and AI Coding Assistants is the story of two competitors. On one side is David Mertz, an expert programmer and the author of the web's most popular Regex tutorial. On the other are the AI powerhouse coding assistants, GitHub Copilot and OpenAI ChatGPT.

The Well-Grounded Java Developer, Second Edition introduces both the modern innovations and timeless fundamentals you need to know to become a Java master. Authors Ben Evans, Martijn Verburg, and Jason Clark distill their decades of experience as Java Champions, veteran developers, and key contributors to the Java ecosystem into this clear and practical audioguide. You’ll discover how Java works under the hood and learn design secrets from Java’s long history.

Data-Oriented Programming is a one-of-a-kind guide that introduces the data-oriented paradigm. This groundbreaking approach represents data with generic immutable data structures. It simplifies state management, eases concurrency, and does away with the common problems you’ll find in object-oriented code. The book presents powerful new ideas through conversations, code snippets, and diagrams that help you quickly grok what’s great about DOP.

Code performance versus simplicity. Delivery speed versus duplication. Flexibility versus maintainability—every decision you make in software engineering involves balancing tradeoffs. In Software Mistakes and Tradeoffs, you’ll learn from costly mistakes that Tomasz Lelek and Jon Skeet have encountered over their impressive careers. You’ll explore real-world scenarios where poor understanding of tradeoffs leads to major problems down the road, so you can preempt your own mistakes with a more thoughtful approach to decision-making.

If you need to learn Spring, look no further than this widely beloved and comprehensive guide! Fully revised for Spring 5.3, and packed with interesting real-world examples to get your hands dirty with Spring. Over the years, Spring in Action has helped tens of thousands of developers get a major productivity boost from Spring. This new edition of the classic best seller covers all of the new features of Spring 5.3 and Spring Boot 2.4 along with examples of reactive programming, Spring Security for REST Services, and bringing reactivity to your databases.

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.

Take the next steps in your data science career! This friendly and hands-on guide shows you how to start mastering Pandas with skills you already know from spreadsheet software.

Learn data science with Python by building five real-world projects! Experiment with card game predictions, tracking disease outbreaks, and more, as you build a flexible and intuitive understanding of data science. In Data Science Bookcamp, you’ll test and build your knowledge of Python with the kind of open-ended problems that professional data scientists work on every day. Downloadable data sets and thoroughly-explained solutions help you lock in what you’ve learned, building your confidence and making you ready for an exciting new data science career. 

A successful pipeline moves data efficiently, minimizing pauses and blockages between tasks, and keeping processes along the way operational. Apache Airflow provides a single customizable environment for building and managing data pipelines, eliminating the need for a hodgepodge collection of tools, snowflake code, and homegrown processes. Using real-world scenarios and examples, this book teaches you how to simplify and automate data pipelines, reduce operational overhead, and smoothly integrate all the technologies in your stack.

Practical techniques for writing code that is robust, reliable, and easy for team members to understand and adapt. In Good Code, Bad Code you’ll learn how to: Think about code like an effective software engineer, write functions that read like well-structured sentences, ensure code is reliable and bug free, effectively unit test code, identify code that can cause problems and improve it, write code that is reusable and adaptable to new requirements, improve your medium and long-term productivity, and save yourself and your team time.