Learning Langchain
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Learning Langchain
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Author : Mayo Oshin
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2025-02-13
Learning Langchain written by Mayo Oshin 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 2025-02-13 with Business & Economics categories.
If you're looking to build production-ready AI applications that can reason and retrieve external data for context-awareness, you'll need to master LangChain—a popular development framework and platform for building, running, and managing agentic applications. LangChain is used by several leading companies, including Zapier, Replit, Databricks, and many more. This guide is an indispensable resource for developers who understand Python or JavaScript but are beginners eager to harness the power of AI. Authors Mayo Oshin and Nuno Campos demystify the use of LangChain through practical insights and in-depth tutorials. Starting with basic concepts, this book shows you step-by-step how to build a production-ready AI agent that uses your data. Harness the power of retrieval-augmented generation (RAG) to enhance the accuracy of LLMs using external up-to-date data Develop and deploy AI applications that interact intelligently and contextually with users Make use of the powerful agent architecture with LangGraph Integrate and manage third-party APIs and tools to extend the functionality of your AI applications Monitor, test, and evaluate your AI applications to improve performance Understand the foundations of LLM app development and how they can be used with LangChain
Learning Langchain
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Author : Mayo Oshin
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2025-02-13
Learning Langchain written by Mayo Oshin 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 2025-02-13 with Computers categories.
If you're looking to build production-ready AI applications that can reason and retrieve external data for context-awareness, you'll need to master--;a popular development framework and platform for building, running, and managing agentic applications. LangChain is used by several leading companies, including Zapier, Replit, Databricks, and many more. This guide is an indispensable resource for developers who understand Python or JavaScript but are beginners eager to harness the power of AI. Authors Mayo Oshin and Nuno Campos demystify the use of LangChain through practical insights and in-depth tutorials. Starting with basic concepts, this book shows you step-by-step how to build a production-ready AI agent that uses your data. Harness the power of retrieval-augmented generation (RAG) to enhance the accuracy of LLMs using external up-to-date data Develop and deploy AI applications that interact intelligently and contextually with users Make use of the powerful agent architecture with LangGraph Integrate and manage third-party APIs and tools to extend the functionality of your AI applications Monitor, test, and evaluate your AI applications to improve performance Understand the foundations of LLM app development and how they can be used with LangChain
Generative Ai With Langchain
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Author : Ben Auffarth
language : en
Publisher: Packt Publishing Ltd
Release Date : 2023-12-22
Generative Ai With Langchain written by Ben Auffarth 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 2023-12-22 with Computers categories.
2024 Edition – Get to grips with the LangChain framework to develop production-ready applications, including agents and personal assistants. The 2024 edition features updated code examples and an improved GitHub repository. Get With Your Book: PDF Copy, AI Assistant, and Next-Gen Reader Free Key Features Learn how to leverage LangChain to work around LLMs’ inherent weaknesses Delve into LLMs with LangChain and explore their fundamentals, ethical dimensions, and application challenges Get better at using ChatGPT and GPT models, from heuristics and training to scalable deployment, empowering you to transform ideas into reality Book DescriptionChatGPT and the GPT models by OpenAI have brought about a revolution not only in how we write and research but also in how we can process information. This book discusses the functioning, capabilities, and limitations of LLMs underlying chat systems, including ChatGPT and Gemini. It demonstrates, in a series of practical examples, how to use the LangChain framework to build production-ready and responsive LLM applications for tasks ranging from customer support to software development assistance and data analysis – illustrating the expansive utility of LLMs in real-world applications. Unlock the full potential of LLMs within your projects as you navigate through guidance on fine-tuning, prompt engineering, and best practices for deployment and monitoring in production environments. Whether you're building creative writing tools, developing sophisticated chatbots, or crafting cutting-edge software development aids, this book will be your roadmap to mastering the transformative power of generative AI with confidence and creativity.What you will learn Create LLM apps with LangChain, like question-answering systems and chatbots Understand transformer models and attention mechanisms Automate data analysis and visualization using pandas and Python Grasp prompt engineering to improve performance Fine-tune LLMs and get to know the tools to unleash their power Deploy LLMs as a service with LangChain and apply evaluation strategies Privately interact with documents using open-source LLMs to prevent data leaks Who this book is for The book is for developers, researchers, and anyone interested in learning more about LangChain. Whether you are a beginner or an experienced developer, this book will serve as a valuable resource if you want to get the most out of LLMs using LangChain. Basic knowledge of Python is a prerequisite, while prior exposure to machine learning will help you follow along more easily.
Build Your Own Ai
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Author : Sebastian Wessel
language : en
Publisher: Sebastian Wessel
Release Date : 2024-11-05
Build Your Own Ai written by Sebastian Wessel and has been published by Sebastian Wessel this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-11-05 with Computers categories.
This comprehensive guide takes you through the journey of creating practical AI applications from scratch, focusing on real-world examples and hands-on techniques to build custom chatbots and AI agents. Inspired by real projects, this book is designed to empower developers with the skills to create their own AI tools, regardless of the model, provider, or programming language. This book does not focus on one provider, language, or framework. This way, you can use what you learn in different situations. We will use free models to learn how to build real-world AI applications. By the end of the book, you will understand how to work with large language models, no matter which model, provider, or programming language you use.
Learn Generative Ai With Pytorch
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Author : Mark Liu
language : en
Publisher: Simon and Schuster
Release Date : 2025-01-28
Learn Generative Ai With Pytorch written by Mark Liu and has been published by Simon and Schuster this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-01-28 with Computers categories.
Learn how generative AI works by building your very own models that can write coherent text, create realistic images, and even make lifelike music. Learn Generative AI with PyTorch teaches the underlying mechanics of generative AI by building working AI models from scratch. Throughout, you’ll use the intuitive PyTorch framework that’s instantly familiar to anyone who’s worked with Python data tools. Along the way, you’ll master the fundamentals of General Adversarial Networks (GANs), Transformers, Large Language Models (LLMs), variational autoencoders, diffusion models, LangChain, and more! In Learn Generative AI with PyTorch you’ll build these amazing models: • A simple English-to-French translator • A text-generating model as powerful as GPT-2 • A diffusion model that produces realistic flower images • Music generators using GANs and Transformers • An image style transfer model • A zero-shot know-it-all agent The generative AI projects you create use the same underlying techniques and technologies as full-scale models like GPT-4 and Stable Diffusion. You don’t need to be a machine learning expert—you can get started with just some basic Python programming skills. About the technology Transformers, Generative Adversarial Networks (GANs), diffusion models, LLMs, and other powerful deep learning patterns have radically changed the way we manipulate text, images, and sound. Generative AI may seem like magic at first, but with a little Python, the PyTorch framework, and some practice, you can build interesting and useful models that will train and run on your laptop. This book shows you how. About the book Learn Generative AI with PyTorch introduces the underlying mechanics of generative AI by helping you build your own working AI models. You’ll begin by creating simple images using a GAN, and then progress to writing a language translation transformer line-by-line. As you work through the fun and fascinating projects, you’ll train models to create anime images, write like Hemingway, make music like Mozart, and more. You just need Python and a few machine learning basics to get started. You’ll learn the rest as you go! What's inside • Build an English-to-French translator • Create a text-generation LLM • Train a diffusion model to produce high-resolution images • Music generators using GANs and Transformers About the reader Examples use simple Python. No deep learning experience required. About the author Mark Liu is the founding director of the Master of Science in Finance program at the University of Kentucky. The technical editor on this book was Emmanuel Maggiori.
Ai Systems And Frameworks
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Author : Ronald Joseph Legarski, Jr.
language : en
Publisher: SolveForce
Release Date : 2025-04-26
Ai Systems And Frameworks written by Ronald Joseph Legarski, Jr. and has been published by SolveForce this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-04-26 with Computers categories.
AI Systems and Frameworks: Designing, Deploying, and Evaluating Intelligent Architectures is a definitive guide for leaders, developers, architects, and policymakers building the future of intelligent systems. Co-authored by Ronald Legarski, an innovator at the intersection of technology and ethics, and Grok, the AI assistant developed by xAI, this book delivers a comprehensive and practical roadmap for navigating the complexities of modern AI deployment. Drawing from global success stories—from retail to healthcare to agriculture—the book explores: Best practices in designing scalable and ethical AI architectures Deploying systems across cloud, edge, and federated environments Evaluating performance, bias, resilience, and sustainability Leading frameworks like TensorFlow, Hugging Face, LangChain, and emerging decentralized AI models Governance principles aligned with regulations like the EU AI Act and global ethical standards In an era where AI investments are exceeding $200 billion annually, AI Systems and Frameworks bridges theory and action, offering the knowledge needed to build AI systems that are not just powerful, but equitable, sustainable, and future-ready. Whether you are an enterprise leader, system architect, startup founder, educator, or policymaker, this book equips you to lead confidently in the intelligent systems revolution.
Neural Networks With Tensorflow And Keras
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Author : Philip Hua
language : en
Publisher: Springer Nature
Release Date : 2024-12-31
Neural Networks With Tensorflow And Keras written by Philip Hua and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-12-31 with Mathematics categories.
Explore the capabilities of machine learning and neural networks. This comprehensive guidebook is tailored for professional programmers seeking to deepen their understanding of neural networks, machine learning techniques, and large language models (LLMs). The book explores the core of machine learning techniques, covering essential topics such as data pre-processing, model selection, and customization. It provides a robust foundation in neural network fundamentals, supplemented by practical case studies and projects. You will explore various network topologies, including Deep Neural Networks (DNN), Recurrent Neural Networks (RNN), Long Short-Term Memory (LSTM) networks, Variational Autoencoders (VAE), Generative Adversarial Networks (GAN), and Large Language Models (LLMs). Each concept is explained with clear, step-by-step instructions and accompanied by Python code examples using the latest versions of TensorFlow and Keras, ensuring a hands-on learning experience. By the end of this book, you will gain practical skills to apply these techniques to solving problems. Whether you are looking to advance your career or enhance your programming capabilities, this book provides the tools and knowledge needed to excel in the rapidly evolving field of machine learning and neural networks. What You Will Learn Grasp the fundamentals of various neural network topologies, including DNN, RNN, LSTM, VAE, GAN, and LLMs Implement neural networks using the latest versions of TensorFlow and Keras, with detailed Python code examples Know the techniques for data pre-processing, model selection, and customization to optimize machine learning models Apply machine learning and neural network techniques in various professional scenarios Who This Book Is For Data scientists, machine learning enthusiasts, and software developers who wish to deepen their understanding of neural networks and machine learning techniques
Mastering Nlp From Foundations To Llms
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Author : Lior Gazit
language : en
Publisher: Packt Publishing Ltd
Release Date : 2024-04-26
Mastering Nlp From Foundations To Llms written by Lior Gazit 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 2024-04-26 with Computers categories.
Enhance your NLP proficiency with modern frameworks like LangChain, explore mathematical foundations and code samples, and gain expert insights into current and future trends Key Features Learn how to build Python-driven solutions with a focus on NLP, LLMs, RAGs, and GPT Master embedding techniques and machine learning principles for real-world applications Understand the mathematical foundations of NLP and deep learning designs Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionDo you want to master Natural Language Processing (NLP) but don’t know where to begin? This book will give you the right head start. Written by leaders in machine learning and NLP, Mastering NLP from Foundations to LLMs provides an in-depth introduction to techniques. Starting with the mathematical foundations of machine learning (ML), you’ll gradually progress to advanced NLP applications such as large language models (LLMs) and AI applications. You’ll get to grips with linear algebra, optimization, probability, and statistics, which are essential for understanding and implementing machine learning and NLP algorithms. You’ll also explore general machine learning techniques and find out how they relate to NLP. Next, you’ll learn how to preprocess text data, explore methods for cleaning and preparing text for analysis, and understand how to do text classification. You’ll get all of this and more along with complete Python code samples. By the end of the book, the advanced topics of LLMs’ theory, design, and applications will be discussed along with the future trends in NLP, which will feature expert opinions. You’ll also get to strengthen your practical skills by working on sample real-world NLP business problems and solutions.What you will learn Master the mathematical foundations of machine learning and NLP Implement advanced techniques for preprocessing text data and analysis Design ML-NLP systems in Python Model and classify text using traditional machine learning and deep learning methods Understand the theory and design of LLMs and their implementation for various applications in AI Explore NLP insights, trends, and expert opinions on its future direction and potential Who this book is for This book is for deep learning and machine learning researchers, NLP practitioners, ML/NLP educators, and STEM students. Professionals working with text data as part of their projects will also find plenty of useful information in this book. Beginner-level familiarity with machine learning and a basic working knowledge of Python will help you get the best out of this book.
Data Labeling In Machine Learning With Python
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Author : Vijaya Kumar Suda
language : en
Publisher: Packt Publishing Ltd
Release Date : 2024-01-31
Data Labeling In Machine Learning With Python written by Vijaya Kumar Suda 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 2024-01-31 with Computers categories.
Take your data preparation, machine learning, and GenAI skills to the next level by learning a range of Python algorithms and tools for data labeling Key Features Generate labels for regression in scenarios with limited training data Apply generative AI and large language models (LLMs) to explore and label text data Leverage Python libraries for image, video, and audio data analysis and data labeling Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionData labeling is the invisible hand that guides the power of artificial intelligence and machine learning. In today’s data-driven world, mastering data labeling is not just an advantage, it’s a necessity. Data Labeling in Machine Learning with Python empowers you to unearth value from raw data, create intelligent systems, and influence the course of technological evolution. With this book, you'll discover the art of employing summary statistics, weak supervision, programmatic rules, and heuristics to assign labels to unlabeled training data programmatically. As you progress, you'll be able to enhance your datasets by mastering the intricacies of semi-supervised learning and data augmentation. Venturing further into the data landscape, you'll immerse yourself in the annotation of image, video, and audio data, harnessing the power of Python libraries such as seaborn, matplotlib, cv2, librosa, openai, and langchain. With hands-on guidance and practical examples, you'll gain proficiency in annotating diverse data types effectively. By the end of this book, you’ll have the practical expertise to programmatically label diverse data types and enhance datasets, unlocking the full potential of your data.What you will learn Excel in exploratory data analysis (EDA) for tabular, text, audio, video, and image data Understand how to use Python libraries to apply rules to label raw data Discover data augmentation techniques for adding classification labels Leverage K-means clustering to classify unsupervised data Explore how hybrid supervised learning is applied to add labels for classification Master text data classification with generative AI Detect objects and classify images with OpenCV and YOLO Uncover a range of techniques and resources for data annotation Who this book is for This book is for machine learning engineers, data scientists, and data engineers who want to learn data labeling methods and algorithms for model training. Data enthusiasts and Python developers will be able to use this book to learn data exploration and annotation using Python libraries. Basic Python knowledge is beneficial but not necessary to get started.
The Complete Obsolete Guide To Generative Ai
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Author : David Clinton
language : en
Publisher: Simon and Schuster
Release Date : 2024-09-17
The Complete Obsolete Guide To Generative Ai written by David Clinton and has been published by Simon and Schuster this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-09-17 with Computers categories.
The last book on AI you’ll ever need. We swear! AI technology moves so fast that this book is probably already out of date! But don’t worry—The Complete Obsolete Guide to Generative AI is still an essential read for anyone who wants to make generative AI into a tool rather than a toy. It shows you how to get the best out of AI no matter what changes come in the future. You’ll be able to use common automation and scripting tools to take AI to a new level, and access raw (and powerful) GPT models via API. Inside The Complete Obsolete Guide to Generative AI you will find: • Just enough background info on AI! What an AI model is how it works • Ways to create text, code, and images for your organization's needs • Training AI models on your local data stores or on the internet • Business intelligence and analytics uses for AI • Building your own custom AI models • Looking ahead to the future of generative AI Where to get started? How about creating exciting images, video, and even audio with AI. Need more? Learn to harness AI to speed up any everyday work task, including writing boilerplate code, creating specialized documents, and analyzing your own data. Push beyond simple ChatGPT prompts! Discover ways to double your productivity and take on projects you never thought were possible! AI—and this book—are here to show you how. About the technology Everything you learn about Generative AI tools like Chat-GPT, Copilot, and Claude becomes obsolete almost immediately. So how do you decide where to spend your time—and your company’s money? This entertaining and unbelievably practical book shows you what you can (and should!) do with AI now and how to roll with the changes as they happen. About the book The Complete Obsolete Guide to Generative AI is a lighthearted introduction to Generative AI written for technology professionals and motivated AI enthusiasts. In it, you’ll get a quick-paced survey of AI techniques for creating code, text, images, and presentations, working with data, and much more. As you explore the hands-on exercises, you’ll build an intuition for how Generative AI can transform your daily work and communication—and maybe even learn how to make peace with your new robot overlords. What's inside • The big picture of Generative AI tools and tech • Creating useful text, code, and images • Writing effective prompts • AI-driven data analytics About the reader Written for developers, admins, and other IT pros. Some examples use simple Python code. About the author David Clinton is an AWS Solutions Architect, a Linux server administrator and a world-renowned expert on obsolescence. The technical editor on this book was Maris Sekar. Table of Contents 1 Understanding generative AI basics 2 Managing generative AI 3 Creating text and code 4 Creating with media resources 5 Feeding data to your generative AI models 6 Prompt engineering: Optimizing your experience 7 Outperforming legacy research and learning tools 8 Understanding stuff better 9 Building and running your own large language model 10 How I learned to stop worrying and love the chaos 11 Experts weigh in on putting AI to work A Important definitions and a brief history B Generative AI resources C Installing Python