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.
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.
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.
Building Analytics Teams. Harnessing analytics and artificial intelligence for business improvement
John K. Thompson
In Building Analytics Teams, John K. Thompson, with his 30+ years of experience and expertise, illustrates the fundamental concepts of building and managing a high-performance analytics team, including what to do, who to hire, projects to undertake, and what to avoid in the journey of building an analytically sound team. The core processes in creating an effective analytics team and the importance of the business decision-making life cycle are explored to help achieve initial and sustainable success.The book demonstrates the various traits of a successful and high-performing analytics team and then delineates the path to achieve this with insights on the mindset, advanced analytics models, and predictions based on data analytics. It also emphasizes the significance of the macro and micro processes required to evolve in response to rapidly changing business needs.The book dives into the methods and practices of managing, developing, and leading an analytics team. Once you've brought the team up to speed, the book explains how to govern executive expectations and select winning projects.By the end of this book, you will have acquired the knowledge to create an effective business analytics team and develop a production environment that delivers ongoing operational improvements for your organization.
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.
Raimon Rafols Montane
To build great user interfaces for your Android apps that go beyond the standard UI elements, you need to use custom Android views. With these, you can give your app a distinctive look and ensure that it functions properly across multiple devices. This book will help you construct a great UI for your apps by teaching you how to create custom Android views. You will start by creating your first Android custom view and go through the design considerations. You will then see how the right choices will enable your custom view to perform seamlessly across multiple platforms and Android versions. You will create custom styleable attributes that work with Android XML layouts, learn to process touch events, define custom attributes, and add properties and events to them. By the end of this book, you will be able to create apps with custom views that are responsive and adaptable to make your app distinctive and an instant hit with its users.