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Author: Mehul Gupta
Publisher: Packt Publishing Ltd
ISBN: 1836201249
Category : Computers
Languages : en
Pages : 152
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Book Description
Learn about LangChain and LLMs with "LangChain in your Pocket," a comprehensive guide to leveraging this innovative framework for building language-based applications. Key Features Step-by-step code explanations with expected outputs for each solution Practical examples and hands-on tutorials for real-world application Detailed discussions on managing and evaluating large language models Book Description"LangChain in your Pocket" offers a detailed exploration into the LangChain framework, designed to enhance your skills in developing sophisticated language understanding models and applications. This book begins with the basics, introducing you to the fundamental concepts of LangChain through a simple "Hello World" example. As you progress, you'll delve into various LangChain modules, learning how to create agents, manage memory, and utilize output parsers effectively. The journey continues as you explore the RAG Framework, vector databases, and their applications in natural language processing, providing you with the tools to tackle common NLP problems efficiently. The book also addresses critical aspects of working with large language models (LLMs), such as prompt engineering, handling hallucinations, and evaluating model outputs. Advanced topics like autonomous AI agents and the integration of LangSmith and LangServe are covered, giving you a holistic view of what you can achieve with LangChain. By the end of this book, you will not only understand the technical aspects of LangChain but also how to apply these principles in real-world scenarios, making it an essential resource for anyone looking to advance their capabilities in AI and language processing.What you will learn Navigate the basic to advanced features of LangChain Build and manage language understanding models and applications Employ advanced prompt engineering techniques Implement and evaluate large language models effectively Develop autonomous AI agents with LangChain Integrate LangSmith and LangServe for enhanced functionality Who this book is for The book "LangChain in your Pocket: Beginner's Guide to Building Generative AI Applications using LLMs" is an excellent resource for individuals new to the world of Generative AI. Whether you are a software developer, data scientist, or student, this beginner-friendly book provides a comprehensive introduction to the LangChain framework and its practical applications. Regardless of your prior experience, this book is a valuable asset for anyone interested in diving into the world of Generative AI and leveraging the power of LangChain.
Author: Mehul Gupta
Publisher: Packt Publishing Ltd
ISBN: 1836201249
Category : Computers
Languages : en
Pages : 152
Get Book Here
Book Description
Learn about LangChain and LLMs with "LangChain in your Pocket," a comprehensive guide to leveraging this innovative framework for building language-based applications. Key Features Step-by-step code explanations with expected outputs for each solution Practical examples and hands-on tutorials for real-world application Detailed discussions on managing and evaluating large language models Book Description"LangChain in your Pocket" offers a detailed exploration into the LangChain framework, designed to enhance your skills in developing sophisticated language understanding models and applications. This book begins with the basics, introducing you to the fundamental concepts of LangChain through a simple "Hello World" example. As you progress, you'll delve into various LangChain modules, learning how to create agents, manage memory, and utilize output parsers effectively. The journey continues as you explore the RAG Framework, vector databases, and their applications in natural language processing, providing you with the tools to tackle common NLP problems efficiently. The book also addresses critical aspects of working with large language models (LLMs), such as prompt engineering, handling hallucinations, and evaluating model outputs. Advanced topics like autonomous AI agents and the integration of LangSmith and LangServe are covered, giving you a holistic view of what you can achieve with LangChain. By the end of this book, you will not only understand the technical aspects of LangChain but also how to apply these principles in real-world scenarios, making it an essential resource for anyone looking to advance their capabilities in AI and language processing.What you will learn Navigate the basic to advanced features of LangChain Build and manage language understanding models and applications Employ advanced prompt engineering techniques Implement and evaluate large language models effectively Develop autonomous AI agents with LangChain Integrate LangSmith and LangServe for enhanced functionality Who this book is for The book "LangChain in your Pocket: Beginner's Guide to Building Generative AI Applications using LLMs" is an excellent resource for individuals new to the world of Generative AI. Whether you are a software developer, data scientist, or student, this beginner-friendly book provides a comprehensive introduction to the LangChain framework and its practical applications. Regardless of your prior experience, this book is a valuable asset for anyone interested in diving into the world of Generative AI and leveraging the power of LangChain.
Author: Jacob Eisenstein
Publisher: MIT Press
ISBN: 0262042843
Category : Computers
Languages : en
Pages : 535
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Book Description
A survey of computational methods for understanding, generating, and manipulating human language, which offers a synthesis of classical representations and algorithms with contemporary machine learning techniques. This textbook provides a technical perspective on natural language processing—methods for building computer software that understands, generates, and manipulates human language. It emphasizes contemporary data-driven approaches, focusing on techniques from supervised and unsupervised machine learning. The first section establishes a foundation in machine learning by building a set of tools that will be used throughout the book and applying them to word-based textual analysis. The second section introduces structured representations of language, including sequences, trees, and graphs. The third section explores different approaches to the representation and analysis of linguistic meaning, ranging from formal logic to neural word embeddings. The final section offers chapter-length treatments of three transformative applications of natural language processing: information extraction, machine translation, and text generation. End-of-chapter exercises include both paper-and-pencil analysis and software implementation. The text synthesizes and distills a broad and diverse research literature, linking contemporary machine learning techniques with the field's linguistic and computational foundations. It is suitable for use in advanced undergraduate and graduate-level courses and as a reference for software engineers and data scientists. Readers should have a background in computer programming and college-level mathematics. After mastering the material presented, students will have the technical skill to build and analyze novel natural language processing systems and to understand the latest research in the field.
Author: Siddhanta Bhatta
Publisher: BPB Publications
ISBN: 9391030432
Category : Computers
Languages : en
Pages : 418
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Book Description
A problem-focused guide for tackling industrial machine learning issues with methods and frameworks chosen by experts. KEY FEATURES ● Popular techniques for problem formulation, data collection, and data cleaning in machine learning. ● Comprehensive and useful machine learning tools such as MLFlow, Streamlit, and many more. ● Covers numerous machine learning libraries, including Tensorflow, FastAI, Scikit-Learn, Pandas, and Numpy. DESCRIPTION This book discusses how to apply machine learning to real-world problems by utilizing real-world data. In this book, you will investigate data sources, become acquainted with data pipelines, and practice how machine learning works through numerous examples and case studies. The book begins with high-level concepts and implementation (with code!) and progresses towards the real-world of ML systems. It briefly discusses various concepts of Statistics and Linear Algebra. You will learn how to formulate a problem, collect data, build a model, and tune it. You will learn about use cases for data analytics, computer vision, and natural language processing. You will also explore nonlinear architecture, thus enabling you to build models with multiple inputs and outputs. You will get trained on creating a machine learning profile, various machine learning libraries, Statistics, and FAST API. Throughout the book, you will use Python to experiment with machine learning libraries such as Tensorflow, Scikit-learn, Spacy, and FastAI. The book will help train our models on both Kaggle and our datasets. WHAT YOU WILL LEARN ● Construct a machine learning problem, evaluate the feasibility, and gather and clean data. ● Learn to explore data first, select, and train machine learning models. ● Fine-tune the chosen model, deploy, and monitor it in production. ● Discover popular models for data analytics, computer vision, and Natural Language Processing. ● Create a machine learning profile and contribute to the community. WHO THIS BOOK IS FOR This book caters to beginners in machine learning, software engineers, and students who want to gain a good understanding of machine learning concepts and create production-ready ML systems. This book assumes you have a beginner-level understanding of Python. TABLE OF CONTENTS 1. Introduction to Machine Learning 2. Problem Formulation in Machine Learning 3. Data Acquisition and Cleaning 4. Exploratory Data Analysis 5. Model Building and Tuning 6. Taking Our Model into Production 7. Data Analytics Use Case 8. Building a Custom Image Classifier from Scratch 9. Building a News Summarization App Using Transformers 10. Multiple Inputs and Multiple Output Models 11. Contributing to the Community 12. Creating Your Project 13. Crash Course in Numpy, Matplotlib, and Pandas 14. Crash Course in Linear Algebra and Statistics 15. Crash Course in FastAPI
Author: Catherine Baab-Muguira
Publisher: Running Press Adult
ISBN: 0762499087
Category : Humor
Languages : en
Pages : 240
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Book Description
When life’s got you down and things aren’t going your way, who better to turn to than Edgar Allan Poe? Discover how to say "nevermore" to your problems in this darkly comedic and refreshing self-help guide. Of all the writers anywhere, Poe would seem to be the least likely person you'd want to turn to for advice. His life was a complete dumpster fire: he had tons of failed relationships; not many people liked him; he was a drunk; he was always broke; he often went hungry; even his own death was somewhat of a mystery. However, that's also precisely the point. Somehow, even when Poe failed, he also persevered. Drawing deeply on his works and life, Catherine Baab-Muguira takes the familiar image of Poe in a new and surprising direction in this darkly inspiring self-help book. Despite what you might think, Edgar Allan Poe somehow is the perfect person to teach you to say "Nevermore, problems!" and show you how to use all the terrible situations, tough breaks, bad luck, and even your darkest emotions in novel and creative ways to make a name for yourself and carve out your own unique, notorious place in the world. An inspirational tale for black sheep everywhere, Poe for Your Problems will teach you how to overcome life’s biggest challenges and succeed at work, love, and art—despite the odds and no matter your flaws.
Author: Emily Robinson
Publisher: Manning
ISBN: 1617296244
Category : Computers
Languages : en
Pages : 352
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Book Description
Summary You are going to need more than technical knowledge to succeed as a data scientist. Build a Career in Data Science teaches you what school leaves out, from how to land your first job to the lifecycle of a data science project, and even how to become a manager. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the technology What are the keys to a data scientist’s long-term success? Blending your technical know-how with the right “soft skills” turns out to be a central ingredient of a rewarding career. About the book Build a Career in Data Science is your guide to landing your first data science job and developing into a valued senior employee. By following clear and simple instructions, you’ll learn to craft an amazing resume and ace your interviews. In this demanding, rapidly changing field, it can be challenging to keep projects on track, adapt to company needs, and manage tricky stakeholders. You’ll love the insights on how to handle expectations, deal with failures, and plan your career path in the stories from seasoned data scientists included in the book. What's inside Creating a portfolio of data science projects Assessing and negotiating an offer Leaving gracefully and moving up the ladder Interviews with professional data scientists About the reader For readers who want to begin or advance a data science career. About the author Emily Robinson is a data scientist at Warby Parker. Jacqueline Nolis is a data science consultant and mentor. Table of Contents: PART 1 - GETTING STARTED WITH DATA SCIENCE 1. What is data science? 2. Data science companies 3. Getting the skills 4. Building a portfolio PART 2 - FINDING YOUR DATA SCIENCE JOB 5. The search: Identifying the right job for you 6. The application: Résumés and cover letters 7. The interview: What to expect and how to handle it 8. The offer: Knowing what to accept PART 3 - SETTLING INTO DATA SCIENCE 9. The first months on the job 10. Making an effective analysis 11. Deploying a model into production 12. Working with stakeholders PART 4 - GROWING IN YOUR DATA SCIENCE ROLE 13. When your data science project fails 14. Joining the data science community 15. Leaving your job gracefully 16. Moving up the ladder
Author: Alberto Artasanchez
Publisher: Packt Publishing Ltd
ISBN: 1839216077
Category : Computers
Languages : en
Pages : 619
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Book Description
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.
Author: Matt Harrison
Publisher: Packt Publishing Ltd
ISBN: 1839218916
Category : Computers
Languages : en
Pages : 627
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Book Description
Use the power of pandas to solve most complex scientific computing problems with ease. Revised for pandas 1.x. Key Features This is the first book on pandas 1.x Practical, easy to implement recipes for quick solutions to common problems in data using pandas Master the fundamentals of pandas to quickly begin exploring any dataset Book DescriptionThe pandas library is massive, and it's common for frequent users to be unaware of many of its more impressive features. The official pandas documentation, while thorough, does not contain many useful examples of how to piece together multiple commands as one would do during an actual analysis. This book guides you, as if you were looking over the shoulder of an expert, through situations that you are highly likely to encounter. This new updated and revised edition provides you with unique, idiomatic, and fun recipes for both fundamental and advanced data manipulation tasks with pandas. Some recipes focus on achieving a deeper understanding of basic principles, or comparing and contrasting two similar operations. Other recipes will dive deep into a particular dataset, uncovering new and unexpected insights along the way. Many advanced recipes combine several different features across the pandas library to generate results.What you will learn Master data exploration in pandas through dozens of practice problems Group, aggregate, transform, reshape, and filter data Merge data from different sources through pandas SQL-like operations Create visualizations via pandas hooks to matplotlib and seaborn Use pandas, time series functionality to perform powerful analyses Import, clean, and prepare real-world datasets for machine learning Create workflows for processing big data that doesn’t fit in memory Who this book is for This book is for Python developers, data scientists, engineers, and analysts. Pandas is the ideal tool for manipulating structured data with Python and this book provides ample instruction and examples. Not only does it cover the basics required to be proficient, but it goes into the details of idiomatic pandas.
Author: Daniel A. Roberts
Publisher: Cambridge University Press
ISBN: 1316519333
Category : Computers
Languages : en
Pages : 473
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Book Description
This volume develops an effective theory approach to understanding deep neural networks of practical relevance.
Author: Atul S. Khot
Publisher: Packt Publishing Ltd
ISBN: 1783985852
Category : Computers
Languages : en
Pages : 298
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Book Description
Grok and perform effective functional programming in Scala About This Book Understand functional programming patterns by comparing them with the traditional object-oriented design patterns Write robust, safer, and better code using the declarative programming paradigm An illustrative guide for programmers to create functional programming patterns with Scala Who This Book Is For If you have done Java programming before and have a basic knowledge of Scala and its syntax, then this book is an ideal choice to help you to understand the context, the traditional design pattern applicable, and the Scala way. Having previous knowledge of design patterns will help, though it is not strictly necessary. What You Will Learn Get to know about functional programming and the value Scala's FP idioms bring to the table Solve day-to-day programming problems using functional programming idioms Cut down the boiler-plate and express patterns simply and elegantly using Scala's concise syntax Tame system complexity by reducing the moving parts Write easier to reason about concurrent code using the actor paradigm and the Akka library Apply recursive thinking and understand how to create solutions without mutation Reuse existing code to compose new behavior Combine the object-oriented and functional programming approaches for effective programming using Scala In Detail Scala is used to construct elegant class hierarchies for maximum code reuse and extensibility and to implement their behavior using higher-order functions. Its functional programming (FP) features are a boon to help you design “easy to reason about” systems to control the growing software complexities. Knowing how and where to apply the many Scala techniques is challenging. Looking at Scala best practices in the context of what you already know helps you grasp these concepts quickly, and helps you see where and why to use them. This book begins with the rationale behind patterns to help you understand where and why each pattern is applied. You will discover what tail recursion brings to your table and will get an understanding of how to create solutions without mutations. We then explain the concept of memorization and infinite sequences for on-demand computation. Further, the book takes you through Scala's stackable traits and dependency injection, a popular technique to produce loosely-coupled software systems. You will also explore how to currying favors to your code and how to simplify it by de-construction via pattern matching. We also show you how to do pipeline transformations using higher order functions such as the pipes and filters pattern. Then we guide you through the increasing importance of concurrent programming and the pitfalls of traditional code concurrency. Lastly, the book takes a paradigm shift to show you the different techniques that functional programming brings to your plate. This book is an invaluable source to help you understand and perform functional programming and solve common programming problems using Scala's programming patterns. Style and approach This is a hands-on guide to Scala's game-changing features for programming. It is filled with many code examples and figures that illustrate various Scala idioms and best practices.
Author: Laurence Gonzales
Publisher: W. W. Norton & Company
ISBN: 0393076571
Category : Psychology
Languages : en
Pages : 324
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Book Description
"Unique among survival books... stunning... enthralling. Deep Survival makes compelling, and chilling, reading."—Penelope Purdy, Denver Post In ?Deep Survival?, Laurence Gonzalez combines hard science and powerful storytelling to illustrate the mysteries of survival, whether in the wilderness or in meeting any of life's great challenges. This gripping narrative, the first book to describe the art and science of survival, will change the way you see the world. Everyone has a mountain to climb. Everyone has a wilderness inside.
