Python
Tiago Antao
Bioinformatics is an active research field that uses a range of simple-to-advanced computations to extract valuable information from biological data, and this book will show you how to manage these tasks using Python.This updated third edition of the Bioinformatics with Python Cookbook begins with a quick overview of the various tools and libraries in the Python ecosystem that will help you convert, analyze, and visualize biological datasets. Next, you'll cover key techniques for next-generation sequencing, single-cell analysis, genomics, metagenomics, population genetics, phylogenetics, and proteomics with the help of real-world examples. You'll learn how to work with important pipeline systems, such as Galaxy servers and Snakemake, and understand the various modules in Python for functional and asynchronous programming. This book will also help you explore topics such as SNP discovery using statistical approaches under high-performance computing frameworks, including Dask and Spark. In addition to this, you’ll explore the application of machine learning algorithms in bioinformatics.By the end of this bioinformatics Python book, you'll be equipped with the knowledge you need to implement the latest programming techniques and frameworks, empowering you to deal with bioinformatics data on every scale.
Oscar Baechler, Xury Greer
Blender is a powerful 3D creation package that supports every aspect of the 3D pipeline. With this book, you'll learn about modeling, rigging, animation, rendering, and much more with the help of some interesting projects.This practical guide, based on the Blender 2.83 LTS version, starts by helping you brush up on your basic Blender skills and getting you acquainted with the software toolset. You’ll use basic modeling tools to understand the simplest 3D workflow by customizing a Viking themed scene. You'll get a chance to see the 3D modeling process from start to finish by building a time machine based on provided concept art. You will design your first 2D character while exploring the capabilities of the new Grease Pencil tools. The book then guides you in creating a sleek modern kitchen scene using EEVEE, Blender’s new state-of-the-art rendering engine. As you advance, you'll explore a variety of 3D design techniques, such as sculpting, retopologizing, unwrapping, baking, painting, rigging, and animating to bring a baby dragon to life.By the end of this book, you'll have learned how to work with Blender to create impressive computer graphics, art, design, and architecture, and you'll be able to use robust Blender tools for your design projects and video games.
Martin Yanev
Unlock the power of AI in your applications with ChatGPT with this practical guide that shows you how to seamlessly integrate OpenAI APIs into your projects, enabling you to navigate complex APIs and ensure seamless functionality with ease.This new edition is updated with key topics such as OpenAI Embeddings, which’ll help you understand the semantic relationships between words and phrases. You’ll find out how to use ChatGPT, Whisper, and DALL-E APIs through 10 AI projects using the latest OpenAI models, GPT-3.5, and GPT-4, with Visual Studio Code as the IDE. Within these projects, you’ll integrate ChatGPT with frameworks and tools such as Flask, Django, Microsoft Office APIs, and PyQt. You’ll get to grips with NLP tasks, build a ChatGPT clone, and create an AI code bug-fixing SaaS app. The chapters will also take you through speech recognition, text-to-speech capabilities, language translation, generating email replies, creating PowerPoint presentations, and fine-tuning ChatGPT, along with adding payment methods by integrating the ChatGPT API with Stripe.By the end of this book, you’ll be able to develop, deploy, and monetize your own groundbreaking applications by harnessing the full potential of ChatGPT APIs.
Building AI Intensive Python Applications. Create intelligent apps with LLMs and vector databases
Rachelle Palmer, Ben Perlmutter, Ashwin Gangadhar, Nicholas...
The era of generative AI is upon us, and this book serves as a roadmap to harness its full potential. With its help, you’ll learn the core components of the AI stack: large language models (LLMs), vector databases, and Python frameworks, and see how these technologies work together to create intelligent applications.The chapters will help you discover best practices for data preparation, model selection, and fine-tuning, and teach you advanced techniques such as retrieval-augmented generation (RAG) to overcome common challenges, such as hallucinations and data leakage. You’ll get a solid understanding of vector databases, implement effective vector search strategies, refine models for accuracy, and optimize performance to achieve impactful results. You’ll also identify and address AI failures to ensure your applications deliver reliable and valuable results. By evaluating and improving the output of LLMs, you’ll be able to enhance their performance and relevance.By the end of this book, you’ll be well-equipped to build sophisticated AI applications that deliver real-world value.
Jan Lukavský
Apache Beam is an open source unified programming model for implementing and executing data processing pipelines, including Extract, Transform, and Load (ETL), batch, and stream processing.This book will help you to confidently build data processing pipelines with Apache Beam. You’ll start with an overview of Apache Beam and understand how to use it to implement basic pipelines. You’ll also learn how to test and run the pipelines efficiently. As you progress, you’ll explore how to structure your code for reusability and also use various Domain Specific Languages (DSLs). Later chapters will show you how to use schemas and query your data using (streaming) SQL. Finally, you’ll understand advanced Apache Beam concepts, such as implementing your own I/O connectors.By the end of this book, you’ll have gained a deep understanding of the Apache Beam model and be able to apply it to solve problems.
Denis Rothman
Standalone LLMs no longer deliver sufficient business value on their own. This guide moves beyond basic chatbots, showing you how to build agentic, ChatGPT-grade systems capable of sophisticated semantic and sentiment analysis, powered by context engineering.You'll design AI controller architectures with multi-user memory retention to dynamically adapt your system to diverse user and system inputs. You'll architect a Retrieval-Augmented Generation system with Pinecone to combine instruction-driven scenarios. Through context engineering, you’ll minimize token usage, maximize response quality, and create systems that reason across complex tasks with precision. You'll enhance your system’s intelligence with multimodal capabilities—image generation, voice interactions, and machine-driven reasoning—leveraging Chain-of-Thought and context chaining to address cross-domain automation challenges. You'll also integrate OpenAI’s suite and DeepSeek-R1 without disrupting your existing GenAISys ecosystem.With context engineering as the backbone, every step becomes a deliberate act of shaping model behavior. Your GenAISys will apply neuroscience-inspired insights to marketing strategies, predict human mobility, integrate smoothly into human workflows, and connect to live external data, all wrapped in a polished, investor-ready interface.
François Voron
FastAPI is a web framework for building APIs with Python 3.6 and its later versions based on standard Python-type hints. With this book, you’ll be able to create fast and reliable data science API backends using practical examples.This book starts with the basics of the FastAPI framework and associated modern Python programming language concepts. You'll be taken through all the aspects of the framework, including its powerful dependency injection system and how you can use it to communicate with databases, implement authentication and integrate machine learning models. Later, you’ll cover best practices relating to testing and deployment to run a high-quality and robust application. You’ll also be introduced to the extensive ecosystem of Python data science packages. As you progress, you’ll learn how to build data science applications in Python using FastAPI. The book also demonstrates how to develop fast and efficient machine learning prediction backends and test them to achieve the best performance. Finally, you’ll see how to implement a real-time face detection system using WebSockets and a web browser as a client.By the end of this FastAPI book, you’ll have not only learned how to implement Python in data science projects but also how to maintain and design them to meet high programming standards with the help of FastAPI.
Will Girten
With so many tools to choose from in today’s data engineering development stack as well as operational complexity, this often overwhelms data engineers, causing them to spend less time gleaning value from their data and more time maintaining complex data pipelines. Guided by a lead specialist solutions architect at Databricks with 10+ years of experience in data and AI, this book shows you how the Delta Live Tables framework simplifies data pipeline development by allowing you to focus on defining input data sources, transformation logic, and output table destinations.This book gives you an overview of the Delta Lake format, the Databricks Data Intelligence Platform, and the Delta Live Tables framework. It teaches you how to apply data transformations by implementing the Databricks medallion architecture and continuously monitor the data quality of your pipelines. You’ll learn how to handle incoming data using the Databricks Auto Loader feature and automate real-time data processing using Databricks workflows. You’ll master how to recover from runtime errors automatically.By the end of this book, you’ll be able to build a real-time data pipeline from scratch using Delta Live Tables, leverage CI/CD tools to deploy data pipeline changes automatically across deployment environments, and monitor, control, and optimize cloud costs.