Building Ai Intensive Python Applications
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Building Ai Intensive Python Applications
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Author : Rachelle Palmer
language : en
Publisher: Packt Publishing Ltd
Release Date : 2024-09-06
Building Ai Intensive Python Applications written by Rachelle Palmer and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-09-06 with Computers categories.
Master retrieval-augmented generation architecture and fine-tune your AI stack, along with discovering real-world use cases and best practices to create powerful AI apps Key Features Get to grips with the fundamentals of LLMs, vector databases, and Python frameworks Implement effective retrieval-augmented generation strategies with MongoDB Atlas Optimize AI models for performance and accuracy with model compression and deployment optimization Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionThe 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.What you will learn Understand the architecture and components of the generative AI stack Explore the role of vector databases in enhancing AI applications Master Python frameworks for AI development Implement Vector Search in AI applications Find out how to effectively evaluate LLM output Overcome common failures and challenges in AI development Who this book is for This book is for software engineers and developers looking to build intelligent applications using generative AI. While the book is suitable for beginners, a basic understanding of Python programming is required to make the most of it.
Building Ai Applications With Microsoft Semantic Kernel
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Author : Lucas A. Meyer
language : en
Publisher: Packt Publishing Ltd
Release Date : 2024-06-21
Building Ai Applications With Microsoft Semantic Kernel written by Lucas A. Meyer and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-06-21 with Computers categories.
Unlock the power of GenAI by effortlessly linking your C# and Python apps with cutting-edge models, orchestrating diverse AI services with finesse, and crafting bespoke applications through immersive, real-world examples Key Features Link your C# and Python applications with the latest AI models from OpenAI Combine and orchestrate different AI services such as text and image generators Create your own AI apps with real-world use case examples that show you how to use basic generative AI, create images, process documents, use a vector database Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionIn 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.What you will learn Write reusable AI prompts and connect to different AI providers Create new plugins that extend the capabilities of AI services Understand how to combine multiple plugins to execute complex actions Orchestrate multiple AI services to accomplish a task Leverage the powerful planner to automatically create appropriate AI calls Use vector databases as additional memory for your AI tasks Deploy your application to ChatGPT, making it available to hundreds of millions of users Who this book is for This book is for beginner-level to experienced .NET or Python software developers who want to quickly incorporate the latest AI technologies into their applications, without having to learn the details of every new AI service. Product managers with some development experience will find this book helpful while creating proof-of-concept applications. This book requires working knowledge of programming basics.
Building Generative Ai Services With Fastapi
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Author : Alireza Parandeh
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2025-04-15
Building Generative Ai Services With Fastapi written by Alireza Parandeh and has been published by "O'Reilly Media, Inc." this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-04-15 with Computers categories.
Ready to build production-grade applications with generative AI? This practical guide takes you through designing and deploying AI services using the FastAPI web framework. Learn how to integrate models that process text, images, audio, and video while seamlessly interacting with databases, filesystems, websites, and APIs. Whether you're a web developer, data scientist, or DevOps engineer, this book equips you with the tools to build scalable, real-time AI applications. Author Alireza Parandeh provides clear explanations and hands-on examples covering authentication, concurrency, caching, and retrieval-augmented generation (RAG) with vector databases. You'll also explore best practices for testing AI outputs, optimizing performance, and securing microservices. With containerized deployment using Docker, you'll be ready to launch AI-powered applications confidently in the cloud. Build generative AI services that interact with databases, filesystems, websites, and APIs Manage concurrency in AI workloads and handle long-running tasks Stream AI-generated outputs in real time via WebSocket and server-sent events Secure services with authentication, content filtering, throttling, and rate limiting Optimize AI performance with caching, batch processing, and fine-tuning techniques Visit the Book's Website.
Explainable Ai With Python
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Author : Leonida Gianfagna
language : en
Publisher: Springer Nature
Release Date : 2021-04-28
Explainable Ai With Python written by Leonida Gianfagna and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-04-28 with Computers categories.
This book provides a full presentation of the current concepts and available techniques to make “machine learning” systems more explainable. The approaches presented can be applied to almost all the current “machine learning” models: linear and logistic regression, deep learning neural networks, natural language processing and image recognition, among the others. Progress in Machine Learning is increasing the use of artificial agents to perform critical tasks previously handled by humans (healthcare, legal and finance, among others). While the principles that guide the design of these agents are understood, most of the current deep-learning models are "opaque" to human understanding. Explainable AI with Python fills the current gap in literature on this emerging topic by taking both a theoretical and a practical perspective, making the reader quickly capable of working with tools and code for Explainable AI. Beginning with examples of what Explainable AI (XAI) is and why it is needed in the field, the book details different approaches to XAI depending on specific context and need. Hands-on work on interpretable models with specific examples leveraging Python are then presented, showing how intrinsic interpretable models can be interpreted and how to produce “human understandable” explanations. Model-agnostic methods for XAI are shown to produce explanations without relying on ML models internals that are “opaque.” Using examples from Computer Vision, the authors then look at explainable models for Deep Learning and prospective methods for the future. Taking a practical perspective, the authors demonstrate how to effectively use ML and XAI in science. The final chapter explains Adversarial Machine Learning and how to do XAI with adversarial examples.
How To Get Into Ai
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Author : Virversity Online Courses
language : en
Publisher: eBookIt.com
Release Date : 2025-02-20
How To Get Into Ai written by Virversity Online Courses and has been published by eBookIt.com this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-02-20 with Computers categories.
Embark on an exciting journey into the world of Artificial Intelligence with our comprehensive online course. Designed for beginners, this course will equip you with the foundational knowledge needed to understand and engage with AI technologies, opening doors to numerous career opportunities. Master the Fundamentals of Artificial Intelligence Gain a solid understanding of AI concepts and terminologies. Learn about the historical background and evolution of Artificial Intelligence. Discover the practical applications and potential of AI in various industries. Acquire skills to identify and analyze AI trends and developments. Introduction to AI: Understanding the Basics of Artificial Intelligence Artificial Intelligence is transforming industries and shaping the future of technology. This course begins with an introduction to the core concepts and definitions that form the basis of AI. You will explore the historical milestones that have led to the current advancements in AI, gaining an appreciation for its rapid evolution. Through engaging lectures and practical examples, you will learn about the diverse applications of AI, from robotics and natural language processing to image recognition and beyond. This course will also provide insights into how AI is being implemented across different sectors, including healthcare, finance, and automotive industries. By the end of this course, you will have developed the ability to critically assess AI trends and contribute to discussions about its future impact. You will be equipped with a foundational understanding that prepares you for more advanced AI studies or to enter AI-related fields. Upon completing this course, you will emerge with a newfound confidence in your ability to engage with AI technologies and a clearer vision of how AI can be leveraged to enhance personal and professional growth.
Ultimate Snowflake Cortex Ai For Generative Ai Applications Design Build And Deploy Generative Ai Solutions With Snowflake Cortex For Real World And Industry Scale Applications
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Author : Krishnan Srinivasan
language : en
Publisher: Orange Education Pvt Limited
Release Date : 2025-06-21
Ultimate Snowflake Cortex Ai For Generative Ai Applications Design Build And Deploy Generative Ai Solutions With Snowflake Cortex For Real World And Industry Scale Applications written by Krishnan Srinivasan and has been published by Orange Education Pvt Limited this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-06-21 with Computers categories.
Power your AI Journey and Build the Future with Snowflake Cortex. Key Features● Build enterprise-ready GenAI apps using Snowflake Cortex tools and APIs.● Implement RAG, AI Agents, and Document AI with real-world precision.● Explore practical Cortex use cases across industries and domains. Book DescriptionSnowflake Cortex is redefining how modern enterprises build, scale, and deploy Generative AI—natively within the data cloud. Ultimate Snowflake Cortex AI for Generative AI Applications is a hands-on, end-to-end guide designed for data professionals, engineers, and technical leaders eager to unlock the full power of Snowflake’s native AI engine. The book begins by grounding you in the fundamentals of AI/ML within the Snowflake ecosystem before diving deep into the architecture, capabilities, and use cases of Snowflake Cortex. As you progress, you’ll explore Cortex’s built-in machine learning functions, dive into prompt engineering, Retrieval-Augmented Generation (RAG), and learn how to leverage LLM functions effectively. You'll gain hands-on experience in fine-tuning models, translating natural language queries into actionable insights, and automating document processing using Cortex’s Document AI. Practical chapters on security, governance, and cost discipline ensure you're prepared for enterprise-scale AI deployment. With real-world case studies and cross-industry applications, this book equips you with both the strategic understanding and technical skills to implement Generative AI at scale. Cortex is the future of enterprise AI—don’t just adapt to it, lead it. What you will learn● Build and deploy Generative AI apps using Snowflake Cortex.● Understand and apply Cortex's built-in LLM functions effectively.● Fine-tune LLMs for domain-specific, enterprise-grade applications.● Use RAG and prompt engineering for accurate AI responses.● Extract insights from structured and unstructured enterprise data.● Automate document workflows using Cortex’s Document AI features.● Solve cross-industry problems with real-world Cortex implementations.
Programming Google App Engine With Python
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Author : Dan Sanderson
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2015-06-29
Programming Google App Engine With Python written by Dan Sanderson and has been published by "O'Reilly Media, Inc." this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-06-29 with Computers categories.
This practical guide shows intermediate and advanced web and mobile app developers how to build highly scalable Python applications in the cloud with Google App Engine. The flagship of Google's Cloud Platform, App Engine hosts your app on infrastructure that grows automatically with your traffic, minimizing up-front costs and accommodating unexpected visitors. You’ll learn hands-on how to perform common development tasks with App Engine services and development tools, including deployment and maintenance. App Engine's Python support includes a fast Python 2.7 interpreter, the standard library, and a WSGI-based runtime environment. Choose from many popular web application frameworks, including Django and Flask. Get a hands-on introduction to App Engine's tools and features, using an example application Simulate App Engine on your development machine with tools from Google Cloud SDK Structure your app into individually addressable modules, each with its own scaling configuration Exploit the power of the scalable Cloud Datastore, using queries, transactions, and data modeling with the ndb library Use Cloud SQL for standard relational databases with App Engine applications Learn how to deploy, manage, and inspect your application on Google infrastructure
Python Textbook
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Author : Manish Soni
language : en
Publisher:
Release Date : 2024-12-04
Python Textbook written by Manish Soni and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-12-04 with Study Aids categories.
This book aims to be your comprehensive guide on your Python programming journey. Whether you are a complete beginner or a seasoned developer looking to deepen your Python knowledge, we have something for everyone. With hands-on examples, real-world projects, and deep explorations of Python's features and capabilities, this book will serve as both a tutorial and a reference.
Artificial Intelligence With Python
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Author : Alberto Artasanchez
language : en
Publisher: Packt Publishing Ltd
Release Date : 2020-01-31
Artificial Intelligence With Python written by Alberto Artasanchez and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-01-31 with Computers categories.
New edition of the bestselling guide to artificial intelligence with Python, updated to Python 3.x, with seven new chapters that cover RNNs, AI and Big Data, fundamental use cases, chatbots, and more. Key FeaturesCompletely updated and revised to Python 3.xNew chapters for AI on the cloud, recurrent neural networks, deep learning models, and feature selection and engineeringLearn more about deep learning algorithms, machine learning data pipelines, and chatbotsBook Description Artificial Intelligence with Python, Second Edition is an updated and expanded version of the bestselling guide to artificial intelligence using the latest version of Python 3.x. Not only does it provide you an introduction to artificial intelligence, this new edition goes further by giving you the tools you need to explore the amazing world of intelligent apps and create your own applications. This edition also includes seven new chapters on more advanced concepts of Artificial Intelligence, including fundamental use cases of AI; machine learning data pipelines; feature selection and feature engineering; AI on the cloud; the basics of chatbots; RNNs and DL models; and AI and Big Data. Finally, this new edition explores various real-world scenarios and teaches you how to apply relevant AI algorithms to a wide swath of problems, starting with the most basic AI concepts and progressively building from there to solve more difficult challenges so that by the end, you will have gained a solid understanding of, and when best to use, these many artificial intelligence techniques. What you will learnUnderstand what artificial intelligence, machine learning, and data science areExplore the most common artificial intelligence use casesLearn how to build a machine learning pipelineAssimilate the basics of feature selection and feature engineeringIdentify the differences between supervised and unsupervised learningDiscover the most recent advances and tools offered for AI development in the cloudDevelop automatic speech recognition systems and chatbotsApply AI algorithms to time series dataWho this book is for The intended audience for this book is Python developers who want to build real-world Artificial Intelligence applications. Basic Python programming experience and awareness of machine learning concepts and techniques is mandatory.
Advancing Social Equity Through Accessible Green Innovation
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Author : William, P.
language : en
Publisher: IGI Global
Release Date : 2025-02-13
Advancing Social Equity Through Accessible Green Innovation written by William, P. and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-02-13 with Technology & Engineering categories.
As the world faces pressing challenges like climate change, resource depletion, and social inequality, green innovation offers solutions to drive positive change for marginalized communities. By creating sustainable technologies, practices, and policies that are affordable and accessible to all, organizations can bridge the gap between environmental progress and social equity. These innovations reduce environmental footprints while providing economic opportunities, improving health outcomes, and enhancing the quality of life for underserved populations. Ensuring these benefits reach everyone, regardless of socio-economic status, will build a more inclusive and sustainable future. Advancing Social Equity Through Accessible Green Innovation explores the latest advancements and methodologies that promote sustainable development. It examines the role of technological advancements such as AI, IoT, and blockchain in driving sustainability initiatives, with emphasis on actionable strategies and practices. This book covers topics such as environmental science, green management, and supply chains, and is a useful resource for business owners, policymakers, government officials, engineers, data scientists, academicians, and researchers.