Informatyka
Martin Yanev
Combining ChatGPT APIs with Python opens doors to building extraordinary AI applications. By leveraging these APIs, you can focus on the application logic and user experience, while ChatGPT’s robust NLP capabilities handle the intricacies of human-like text understanding and generation.This book is a guide for beginners to master the ChatGPT, Whisper, and DALL-E APIs by building ten innovative AI projects. These projects offer practical experience in integrating ChatGPT with frameworks and tools such as Flask, Django, Microsoft Office APIs, and PyQt.Throughout this book, you’ll get to grips with performing NLP tasks, building a ChatGPT clone, and creating an AI-driven code bug fixing SaaS application. You’ll also cover speech recognition, text-to-speech functionalities, language translation, and generation of email replies and PowerPoint presentations. This book teaches you how to fine-tune ChatGPT and generate AI art using DALL-E APIs, and then offers insights into selling your apps by integrating ChatGPT API with Stripe. With practical examples available on GitHub, the book gradually progresses from easy to advanced topics, cultivating the expertise required to develop, deploy, and monetize your own groundbreaking applications by harnessing the full potential of ChatGPT APIs.
Lucas A. Meyer
In the fast-paced world of AI, developers are constantly seeking efficient ways to integrate AI capabilities into their apps. Microsoft Semantic Kernel simplifies this process by using the GenAI features from Microsoft and OpenAI.Written by Lucas A. Meyer, a Principal Research Scientist in Microsoft’s AI for Good Lab, this book helps you get hands on with Semantic Kernel. It begins by introducing you to different generative AI services such as GPT-3.5 and GPT-4, demonstrating their integration with Semantic Kernel. You’ll then learn to craft prompt templates for reuse across various AI services and variables. Next, you’ll learn how to add functionality to Semantic Kernel by creating your own plugins. The second part of the book shows you how to combine multiple plugins to execute complex actions, and how to let Semantic Kernel use its own AI to solve complex problems by calling plugins, including the ones made by you. The book concludes by teaching you how to use vector databases to expand the memory of your AI services and how to help AI remember the context of earlier requests. You’ll also be guided through several real-world examples of applications, such as RAG and custom GPT agents.By the end of this book, you'll have gained the knowledge you need to start using Semantic Kernel to add AI capabilities to your applications.
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.
Giorgio Boa, Fabio Biondi
In Building AI-Powered Apps with Angular, you'll embark on an end-to-end journey to revolutionize web development with artificial intelligence. This hands-on guide shows you how to integrate cutting-edge AI capabilities, particularly Large Language Models (LLMs) like Google Gemini and multimodal agents, directly into your Angular applications.Starting with AI/ML fundamentals and an introduction to Google Gemini using Node.js, you’ll quickly progress to building sophisticated AI features within your Angular frontend. You’ll create dynamic content, design intelligent multi-turn chat interfaces, and harness multimodal AI to analyze and generate rich media such as images and videos.The journey extends beyond the frontend. You’ll build robust backends with Angular Server-Side Rendering and Genkit, enabling seamless communication with AI models. You’ll also implement advanced search capabilities using Retrieval Augmented Generation (RAG) and Firestore and learn how to deploy your AI-powered Angular app to the cloud.By the end of the book, you'll have the skills to design, develop, and deploy innovative and intelligent Angular applications that leverage the full potential of AI.
Building an API Product. Design, implement, release, and maintain API products that meet user needs
Bruno Pedro
The exponential increase in the number of APIs is evidence of their widespread adoption by companies seeking to deliver value to users across diverse industries, making the art of building successful APIs an invaluable skill for anyone involved in product development. With this comprehensive guide, you’ll walk through the entire process of planning, designing, implementing, releasing, and maintaining successful API products. You’ll start by exploring all aspects of APIs, including their types, technologies, protocols, and lifecycle stages. Next, you’ll learn how to define an API strategy and identify business objectives, user personas, and jobs-to-be-done (JTBD). With these skills, you’ll delve into designing and validating API capabilities to create a machine-readable API definition. As you advance, the book helps you understand how to choose the right language and framework for securely releasing an API server and offers insights into analyzing API usage metrics, improving performance, and creating compelling documentation that users love. Finally, you’ll discover ways to support users, manage versions, and communicate changes or the retirement of an API.By the end of this API development book, you’ll have the confidence and skills to create API products that truly stand out in the market.
Building an Application Development Framework. Empower your engineering teams with custom frameworks
Ivan Padabed, Roman Voronin
Transform the way you build software with ADFs designed for agility and success. In today's competitive tech landscape, inefficient software development processes can hold your organizational back. Written by two tech experts who have architected success across many cutting-edge startups, Building an Application Development addresses this challenge by introducing you to the power of ADFs. You’ll explore core concepts, uncover the strategic advantages of ADFs, and learn how to architect a custom framework tailored to your specific needs and business goals.Through practical guidance and real-world case studies, you'll gain mastery over critical elements, such as version control, packaging, testing, and documentation. The book emphasizes fostering an extensible ecosystem for your ADF, empowering your engineering teams to navigate the ever-evolving technological landscape with confidence and agility.Ivan Padabed and Roman Voronin bring their experience of transforming complex engineering challenges into scalable solutions to equip you with the knowledge you need to drive efficiency, enhance quality, and achieve long-term success through a powerful, reusable ADF that can adapt to changing requirements.By the end of this book, you'll be able to unlock the potential of your development processes and elevate your team's productivity.
Joshua Arvin Lat
The significant increase in the number of cloud-related threats and issues has led to a surge in the demand for cloud security professionals. This book will help you set up vulnerable-by-design environments in the cloud to minimize the risks involved while learning all about cloud penetration testing and ethical hacking.This step-by-step guide begins by helping you design and build penetration testing labs that mimic modern cloud environments running on AWS, Azure, and Google Cloud Platform (GCP). Next, you’ll find out how to use infrastructure as code (IaC) solutions to manage a variety of lab environments in the cloud. As you advance, you’ll discover how generative AI tools, such as ChatGPT, can be leveraged to accelerate the preparation of IaC templates and configurations. You’ll also learn how to validate vulnerabilities by exploiting misconfigurations and vulnerabilities using various penetration testing tools and techniques. Finally, you’ll explore several practical strategies for managing the complexity, cost, and risks involved when dealing with penetration testing lab environments in the cloud.By the end of this penetration testing book, you’ll be able to design and build cost-effective vulnerable cloud lab environments where you can experiment and practice different types of attacks and penetration testing techniques.
Amar Deep Singh
Reliable automation is crucial for any code change going into production. A release pipeline enables you to deliver features for your users efficiently and promptly. AWS CodePipeline, with its powerful integration and automation capabilities of building, testing, and deployment, offers a unique solution to common software delivery issues such as outages during deployment, a lack of standard delivery mechanisms, and challenges faced in creating sustainable pipelines.You’ll begin by developing a Java microservice and using AWS services such as CodeCommit, CodeArtifact, and CodeGuru to manage and review the source code. You’ll then learn to use the AWS CodeBuild service to build code and deploy it to AWS infrastructure and container services using the CodeDeploy service. As you advance, you’ll find out how to provision cloud infrastructure using CloudFormation templates and Terraform. The concluding chapters will show you how to combine all these AWS services to create a reliable and automated CodePipeline for delivering microservices from source code check-in to deployment without any downtime. Finally, you’ll discover how to integrate AWS CodePipeline with third-party services such as Bitbucket, Blazemeter, Snyk, and Jenkins.By the end of this microservices book, you’ll have gained the hands-on skills to build release pipelines for your applications.