Building Levels in Unity. Create exciting 3D game worlds with Unity

Volodymyr Gerasimov

Building LLM Powered Applications. Create intelligent apps and agents with large language models

Valentina Alto

Building LLM Powered Applications delves into the fundamental concepts, cutting-edge technologies, and practical applications that LLMs offer, ultimately paving the way for the emergence of large foundation models (LFMs) that extend the boundaries of AI capabilities.The book begins with an in-depth introduction to LLMs. We then explore various mainstream architectural frameworks, including both proprietary models (GPT 3.5/4) and open-source models (Falcon LLM), and analyze their unique strengths and differences. Moving ahead, with a focus on the Python-based, lightweight framework called LangChain, we guide you through the process of creating intelligent agents capable of retrieving information from unstructured data and engaging with structured data using LLMs and powerful toolkits. Furthermore, the book ventures into the realm of LFMs, which transcend language modeling to encompass various AI tasks and modalities, such as vision and audio.Whether you are a seasoned AI expert or a newcomer to the field, this book is your roadmap to unlock the full potential of LLMs and forge a new era of intelligent machines.

Building Low Latency Applications with C++. Develop a complete low latency trading ecosystem from scratch using modern C++

Sourav Ghosh

C++ is meticulously designed with efficiency, performance, and flexibility as its core objectives. However, real-time low latency applications demand a distinct set of requirements, particularly in terms of performance latencies.With this book, you’ll gain insights into the performance requirements for low latency applications and the C++ features critical to achieving the required performance latencies. You’ll also solidify your understanding of the C++ principles and techniques as you build a low latency system in C++ from scratch.You’ll understand the similarities between such applications, recognize the impact of performance latencies on business, and grasp the reasons behind the extensive efforts invested in minimizing latencies. Using a step-by-step approach, you’ll embark on a low latency app development journey by building an entire electronic trading system, encompassing a matching engine, market data handlers, order gateways, and trading algorithms, all in C++. Additionally, you’ll get to grips with measuring and optimizing the performance of your trading system.By the end of this book, you’ll have a comprehensive understanding of how to design and build low latency applications in C++ from the ground up, while effectively minimizing performance latencies.

Building Low-Code Applications with Mendix. Discover best practices and expert techniques to simplify enterprise web development

Bryan Kenneweg, Imran Kasam, Micah McMullen, Michael Guido

Low-code is a visual approach to application development. It enables developers of varying experience levels to create web and mobile apps using drag-and-drop components and model-driven logic through a graphic user interface. Mendix is among the fastest-growing platforms that enable low-code enthusiasts to put their software ideas into practice without having to write much code, and Building Low-Code Applications with Mendix will help you get up and running with the process using examples and practice projects.The book starts with an introduction to Mendix, along with the reasons for using this platform and its tools for creating your first app. As you progress, you’ll explore Mendix Studio Pro, the visual environment that will help you learn Mendix app creation. Once you have your working app ready, you’ll understand how to enhance it with custom business logic and rules. Next, you’ll find out how to defend your app against bad data, troubleshoot and debug it, and finally, connect it with real-world business platforms. You’ll build practical skills as the book is filled with examples, real-world scenarios, and explanations of the tools needed to help you build low-code apps successfully.By the end of this book, you’ll have understood the concept of low-code development, learned how to use Mendix effectively, and developed a working app.

Building Machine Learning Systems with Python. Expand your Python knowledge and learn all about machine-learning libraries in this user-friendly manual. ML is the next big breakthrough in technology and this book will give you the head-start you need

Willi Richert, Luis Pedro Coelho

Machine learning, the field of building systems that learn from data, is exploding on the Web and elsewhere. Python is a wonderful language in which to develop machine learning applications. As a dynamic language, it allows for fast exploration and experimentation and an increasing number of machine learning libraries are developed for Python.Building Machine Learning system with Python shows you exactly how to find patterns through raw data. The book starts by brushing up on your Python ML knowledge and introducing libraries, and then moves on to more serious projects on datasets, Modelling, Recommendations, improving recommendations through examples and sailing through sound and image processing in detail. Using open-source tools and libraries, readers will learn how to apply methods to text, images, and sounds. You will also learn how to evaluate, compare, and choose machine learning techniques. Written for Python programmers, Building Machine Learning Systems with Python teaches you how to use open-source libraries to solve real problems with machine learning. The book is based on real-world examples that the user can build on.Readers will learn how to write programs that classify the quality of StackOverflow answers or whether a music file is Jazz or Metal. They will learn regression, which is demonstrated on how to recommend movies to users. Advanced topics such as topic modeling (finding a text's most important topics), basket analysis, and cloud computing are covered as well as many other interesting aspects.Building Machine Learning Systems with Python will give you the tools and understanding required to build your own systems, which are tailored to solve your problems.

Building Machine Learning Systems with Python. Explore machine learning and deep learning techniques for building intelligent systems using scikit-learn and TensorFlow - Third Edition

Luis Pedro Coelho, Willi Richert, Matthieu Brucher

Machine learning enables systems to make predictions based on historical data. Python is one of the most popular languages used to develop machine learning applications, thanks to its extensive library support. This updated third edition of Building Machine Learning Systems with Python helps you get up to speed with the latest trends in artificial intelligence (AI).With this guide’s hands-on approach, you’ll learn to build state-of-the-art machine learning models from scratch. Complete with ready-to-implement code and real-world examples, the book starts by introducing the Python ecosystem for machine learning. You’ll then learn best practices for preparing data for analysis and later gain insights into implementing supervised and unsupervised machine learning techniques such as classification, regression and clustering. As you progress, you’ll understand how to use Python’s scikit-learn and TensorFlow libraries to build production-ready and end-to-end machine learning system models, and then fine-tune them for high performance.By the end of this book, you’ll have the skills you need to confidently train and deploy enterprise-grade machine learning models in Python.

Building Mapping Applications with QGIS. Create your own sophisticated applications to analyze and display geospatial information using QGIS and Python

Erik Westra

Building Micro Frontends with React 18. Develop and deploy scalable applications using micro frontend strategies

Vinci J Rufus

Although deservedly popular and highly performant tools for building modern web applications, React and single-page applications (SPAs) become more and more sluggish as your applications and teams grow. To solve this problem, many large web apps have started to break down monolith SPAs into independently deployable smaller apps and components—a pattern called micro frontends. But micro frontends aren't a perfect solution, but rather a double-edged sword. This book teaches you how to architect and build them with the right principles to reap all the benefits without the pitfalls.This book will take you through two patterns of building micro frontends, the multi-SPA pattern and the micro apps pattern. You’ll find out which patterns to use and when, as well as take a look at the nuances of deploying these micro frontends using cloud-native technologies such as Kubernetes and Firebase. With the help of this book, you’ll gain an in-depth understanding of state management, solving problems with routing, and deployment strategies between the different micro frontends.By the end of this book, you’ll have learned how to design and build a React-based micro frontend application using module federation and deploy it to the cloud efficiently.