Building Llm Applications With Python A Practical Guide

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Building LLM Applications with Python: A Practical Guide

Author : Anand Vemula
Publisher : Anand Vemula
ISBN 13 :
Total Pages : 42 pages
Book Rating : 4./5 ( download)

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Book Synopsis Building LLM Applications with Python: A Practical Guide by : Anand Vemula

Download or read book Building LLM Applications with Python: A Practical Guide written by Anand Vemula and published by Anand Vemula. This book was released on with total page 42 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book equips you to harness the remarkable capabilities of Large Language Models (LLMs) using Python. Part I unveils the world of LLMs. You'll delve into their inner workings, explore different LLM types, and discover their exciting applications in various fields. Part II dives into the practical side of things. We'll guide you through setting up your Python environment and interacting with LLMs. Learn to craft effective prompts to get the most out of LLMs and understand the different response formats they can generate. Part III gets you building! We'll explore how to leverage LLMs for creative text generation, from poems and scripts to code snippets. Craft effective question-answering systems and build engaging chatbots – the possibilities are endless! Part IV empowers you to maintain and improve your LLM creations. We'll delve into debugging techniques to identify and resolve issues. Learn to track performance and implement optimizations to ensure your LLM applications run smoothly. This book doesn't shy away from the bigger picture. The final chapter explores the ethical considerations of LLMs, addressing bias and promoting responsible use of this powerful technology. By the end of this journey, you'll be equipped to unlock the potential of LLMs with Python and contribute to a future brimming with exciting possibilities.

Building Data-Driven Applications with LlamaIndex

Author : Andrei Gheorghiu
Publisher : Packt Publishing Ltd
ISBN 13 : 1805124404
Total Pages : 368 pages
Book Rating : 4.8/5 (51 download)

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Book Synopsis Building Data-Driven Applications with LlamaIndex by : Andrei Gheorghiu

Download or read book Building Data-Driven Applications with LlamaIndex written by Andrei Gheorghiu and published by Packt Publishing Ltd. This book was released on 2024-05-10 with total page 368 pages. Available in PDF, EPUB and Kindle. Book excerpt: Solve real-world problems easily with artificial intelligence (AI) using the LlamaIndex data framework to enhance your LLM-based Python applications Key Features Examine text chunking effects on RAG workflows and understand security in RAG app development Discover chatbots and agents and learn how to build complex conversation engines Build as you learn by applying the knowledge you gain to a hands-on project Book DescriptionDiscover the immense potential of Generative AI and Large Language Models (LLMs) with this comprehensive guide. Learn to overcome LLM limitations, such as contextual memory constraints, prompt size issues, real-time data gaps, and occasional ‘hallucinations’. Follow practical examples to personalize and launch your LlamaIndex projects, mastering skills in ingesting, indexing, querying, and connecting dynamic knowledge bases. From fundamental LLM concepts to LlamaIndex deployment and customization, this book provides a holistic grasp of LlamaIndex's capabilities and applications. By the end, you'll be able to resolve LLM challenges and build interactive AI-driven applications using best practices in prompt engineering and troubleshooting Generative AI projects.What you will learn Understand the LlamaIndex ecosystem and common use cases Master techniques to ingest and parse data from various sources into LlamaIndex Discover how to create optimized indexes tailored to your use cases Understand how to query LlamaIndex effectively and interpret responses Build an end-to-end interactive web application with LlamaIndex, Python, and Streamlit Customize a LlamaIndex configuration based on your project needs Predict costs and deal with potential privacy issues Deploy LlamaIndex applications that others can use Who this book is for This book is for Python developers with basic knowledge of natural language processing (NLP) and LLMs looking to build interactive LLM applications. Experienced developers and conversational AI developers will also benefit from the advanced techniques covered in the book to fully unleash the capabilities of the framework.

Unveiling LangChain and LLM for Python Developers

Author : Matthew D Passmore
Publisher : Independently Published
ISBN 13 :
Total Pages : 0 pages
Book Rating : 4.3/5 (326 download)

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Book Synopsis Unveiling LangChain and LLM for Python Developers by : Matthew D Passmore

Download or read book Unveiling LangChain and LLM for Python Developers written by Matthew D Passmore and published by Independently Published. This book was released on 2024-07-09 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Unlock the power of Language Models and revolutionize your web development skills with "Unveiling LangChain and LLM for Python Developers: Your Beginner-Friendly Guide to Building Intelligent, Scalable, and Unique Web Applications (LLMs Decoded with TensorFlow, Hugging Face, and More)." In this comprehensive guide, dive into the world of Large Language Models (LLMs) and learn how to leverage their capabilities to create cutting-edge web applications. Whether you're a seasoned developer or just starting your journey, this book offers a clear and practical approach to mastering LLMs using popular frameworks like TensorFlow and Hugging Face. **What You'll Discover: ** - **Foundations of LLMs**: Understand the basics of language models, their architectures, and how they process and generate human-like text. - **Hands-On Tutorials**: Step-by-step instructions to integrate LLMs into your Python projects, complete with code examples and detailed explanations. - **Scalable Solutions**: Learn how to build applications that can handle large-scale data and deliver real-time performance. - **Advanced Techniques**: Explore sophisticated topics such as fine-tuning pre-trained models, optimizing performance, and deploying LLMs in production environments. - **Practical Applications**: Real-world case studies demonstrating how LLMs can be used in chatbots, content generation, sentiment analysis, and more. With a focus on practical knowledge and real-world applications, this book equips you with the skills to create intelligent, scalable, and unique web applications that stand out in today's competitive landscape. Whether you're aiming to enhance user experience, automate content creation, or simply explore the potential of artificial intelligence in web development, "Unveiling LangChain and LLM for Python Developers" is your essential guide to the future of web development

Building LLM Toolkit

Author : Lou Jackson
Publisher : Independently Published
ISBN 13 :
Total Pages : 0 pages
Book Rating : 4.3/5 (287 download)

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Book Synopsis Building LLM Toolkit by : Lou Jackson

Download or read book Building LLM Toolkit written by Lou Jackson and published by Independently Published. This book was released on 2024-06-17 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is a practical guide to using large language models (LLMs) for real-world tasks. It teaches you how to build, improve, and use LLMs for real projects. The book covers a lot, including: * How to build different parts of LLMs, like transformer models. * Techniques for giving LLMs instructions to get the desired results. * How to adjust LLMs to work on specific data sets. * Creating systems that combine searching information and generating new text. The book also explains how to deal with the challenges of using LLMs in real applications, such as making them run faster, storing them efficiently, and using cloud services. You'll also learn how to make sure your LLMs are accurate, reliable, and avoid biases. Finally, the book covers legal and ethical considerations, like data privacy and fairness in LLM outputs. This book is useful for anyone who wants to learn about LLMs, from engineers and researchers to developers and data scientists. Even if you're new to LLMs, this book will give you a strong foundation.

Building LLM Powered Applications

Author : Valentina Alto
Publisher : Packt Publishing Ltd
ISBN 13 : 1835462634
Total Pages : 343 pages
Book Rating : 4.8/5 (354 download)

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Book Synopsis Building LLM Powered Applications by : Valentina Alto

Download or read book Building LLM Powered Applications written by Valentina Alto and published by Packt Publishing Ltd. This book was released on 2024-05-22 with total page 343 pages. Available in PDF, EPUB and Kindle. Book excerpt: Get hands-on with GPT 3.5, GPT 4, LangChain, Llama 2, Falcon LLM and more, to build LLM-powered sophisticated AI applications Key Features Embed LLMs into real-world applications Use LangChain to orchestrate LLMs and their components within applications Grasp basic and advanced techniques of prompt engineering Book DescriptionBuilding LLM Powered Applications delves into the fundamental concepts, cutting-edge technologies, and practical applications that LLMs offer, ultimately paving the way for the emergence of large foundation models (LFMs) that extend the boundaries of AI capabilities. The book begins with an in-depth introduction to LLMs. We then explore various mainstream architectural frameworks, including both proprietary models (GPT 3.5/4) and open-source models (Falcon LLM), and analyze their unique strengths and differences. Moving ahead, with a focus on the Python-based, lightweight framework called LangChain, we guide you through the process of creating intelligent agents capable of retrieving information from unstructured data and engaging with structured data using LLMs and powerful toolkits. Furthermore, the book ventures into the realm of LFMs, which transcend language modeling to encompass various AI tasks and modalities, such as vision and audio. Whether you are a seasoned AI expert or a newcomer to the field, this book is your roadmap to unlock the full potential of LLMs and forge a new era of intelligent machines.What you will learn Explore the core components of LLM architecture, including encoder-decoder blocks and embeddings Understand the unique features of LLMs like GPT-3.5/4, Llama 2, and Falcon LLM Use AI orchestrators like LangChain, with Streamlit for the frontend Get familiar with LLM components such as memory, prompts, and tools Learn how to use non-parametric knowledge and vector databases Understand the implications of LFMs for AI research and industry applications Customize your LLMs with fine tuning Learn about the ethical implications of LLM-powered applications Who this book is for Software engineers and data scientists who want hands-on guidance for applying LLMs to build applications. The book will also appeal to technical leaders, students, and researchers interested in applied LLM topics. We don’t assume previous experience with LLM specifically. But readers should have core ML/software engineering fundamentals to understand and apply the content.

Practical Machine Learning with Python

Author : Dipanjan Sarkar
Publisher : Apress
ISBN 13 : 1484232070
Total Pages : 545 pages
Book Rating : 4.4/5 (842 download)

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Book Synopsis Practical Machine Learning with Python by : Dipanjan Sarkar

Download or read book Practical Machine Learning with Python written by Dipanjan Sarkar and published by Apress. This book was released on 2017-12-20 with total page 545 pages. Available in PDF, EPUB and Kindle. Book excerpt: Master the essential skills needed to recognize and solve complex problems with machine learning and deep learning. Using real-world examples that leverage the popular Python machine learning ecosystem, this book is your perfect companion for learning the art and science of machine learning to become a successful practitioner. The concepts, techniques, tools, frameworks, and methodologies used in this book will teach you how to think, design, build, and execute machine learning systems and projects successfully. Practical Machine Learning with Python follows a structured and comprehensive three-tiered approach packed with hands-on examples and code. Part 1 focuses on understanding machine learning concepts and tools. This includes machine learning basics with a broad overview of algorithms, techniques, concepts and applications, followed by a tour of the entire Python machine learning ecosystem. Brief guides for useful machine learning tools, libraries and frameworks are also covered. Part 2 details standard machine learning pipelines, with an emphasis on data processing analysis, feature engineering, and modeling. You will learn how to process, wrangle, summarize and visualize data in its various forms. Feature engineering and selection methodologies will be covered in detail with real-world datasets followed by model building, tuning, interpretation and deployment. Part 3 explores multiple real-world case studies spanning diverse domains and industries like retail, transportation, movies, music, marketing, computer vision and finance. For each case study, you will learn the application of various machine learning techniques and methods. The hands-on examples will help you become familiar with state-of-the-art machine learning tools and techniques and understand what algorithms are best suited for any problem. Practical Machine Learning with Python will empower you to start solving your own problems with machine learning today! What You'll Learn Execute end-to-end machine learning projects and systems Implement hands-on examples with industry standard, open source, robust machine learning tools and frameworks Review case studies depicting applications of machine learning and deep learning on diverse domains and industries Apply a wide range of machine learning models including regression, classification, and clustering. Understand and apply the latest models and methodologies from deep learning including CNNs, RNNs, LSTMs and transfer learning. Who This Book Is For IT professionals, analysts, developers, data scientists, engineers, graduate students

Hands-On Natural Language Processing with Python

Author : Rajesh Arumugam
Publisher : Packt Publishing Ltd
ISBN 13 : 1789135915
Total Pages : 307 pages
Book Rating : 4.7/5 (891 download)

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Book Synopsis Hands-On Natural Language Processing with Python by : Rajesh Arumugam

Download or read book Hands-On Natural Language Processing with Python written by Rajesh Arumugam and published by Packt Publishing Ltd. This book was released on 2018-07-18 with total page 307 pages. Available in PDF, EPUB and Kindle. Book excerpt: Foster your NLP applications with the help of deep learning, NLTK, and TensorFlow Key Features Weave neural networks into linguistic applications across various platforms Perform NLP tasks and train its models using NLTK and TensorFlow Boost your NLP models with strong deep learning architectures such as CNNs and RNNs Book Description Natural language processing (NLP) has found its application in various domains, such as web search, advertisements, and customer services, and with the help of deep learning, we can enhance its performances in these areas. Hands-On Natural Language Processing with Python teaches you how to leverage deep learning models for performing various NLP tasks, along with best practices in dealing with today’s NLP challenges. To begin with, you will understand the core concepts of NLP and deep learning, such as Convolutional Neural Networks (CNNs), recurrent neural networks (RNNs), semantic embedding, Word2vec, and more. You will learn how to perform each and every task of NLP using neural networks, in which you will train and deploy neural networks in your NLP applications. You will get accustomed to using RNNs and CNNs in various application areas, such as text classification and sequence labeling, which are essential in the application of sentiment analysis, customer service chatbots, and anomaly detection. You will be equipped with practical knowledge in order to implement deep learning in your linguistic applications using Python's popular deep learning library, TensorFlow. By the end of this book, you will be well versed in building deep learning-backed NLP applications, along with overcoming NLP challenges with best practices developed by domain experts. What you will learn Implement semantic embedding of words to classify and find entities Convert words to vectors by training in order to perform arithmetic operations Train a deep learning model to detect classification of tweets and news Implement a question-answer model with search and RNN models Train models for various text classification datasets using CNN Implement WaveNet a deep generative model for producing a natural-sounding voice Convert voice-to-text and text-to-voice Train a model to convert speech-to-text using DeepSpeech Who this book is for Hands-on Natural Language Processing with Python is for you if you are a developer, machine learning or an NLP engineer who wants to build a deep learning application that leverages NLP techniques. This comprehensive guide is also useful for deep learning users who want to extend their deep learning skills in building NLP applications. All you need is the basics of machine learning and Python to enjoy the book.

Machine Learning With Python

Author : Rosalba Wable
Publisher : Independently Published
ISBN 13 :
Total Pages : 124 pages
Book Rating : 4.7/5 (117 download)

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Book Synopsis Machine Learning With Python by : Rosalba Wable

Download or read book Machine Learning With Python written by Rosalba Wable and published by Independently Published. This book was released on 2021-02-20 with total page 124 pages. Available in PDF, EPUB and Kindle. Book excerpt: Machine Learning (ML) is basically that field of computer science with the help of which computer systems can provide sense to data in much the same way as human beings do. In simple words, ML is a type of artificial intelligence that extract patterns out of raw data by using an algorithm or method. In this step-by-step guide you will learn: - To code machine learning models using a range of supervised learning algorithms including logistic regression, gradient boosting, and decision trees - Clean and inspect your data using free machine learning libraries - Visualize relationships in your dataset including Heatmaps and Pairplots with just a few lines of code - Develop your expertise in managing data using Python

CRAFTING PYTHON REST APIS WITH FLASK

Author : GOPI. P
Publisher :
ISBN 13 : 9781803239279
Total Pages : pages
Book Rating : 4.2/5 (392 download)

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Book Synopsis CRAFTING PYTHON REST APIS WITH FLASK by : GOPI. P

Download or read book CRAFTING PYTHON REST APIS WITH FLASK written by GOPI. P and published by . This book was released on 2022 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Building Web Apps with Python and Flask

Author : Malhar Lathkar
Publisher : BPB Publications
ISBN 13 : 9389898838
Total Pages : 275 pages
Book Rating : 4.3/5 (898 download)

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Book Synopsis Building Web Apps with Python and Flask by : Malhar Lathkar

Download or read book Building Web Apps with Python and Flask written by Malhar Lathkar and published by BPB Publications. This book was released on 2021-03-12 with total page 275 pages. Available in PDF, EPUB and Kindle. Book excerpt: A practical guide for the rapid web application development with Flask KEY FEATURESÊ _ Expert-led coverage of core capabilities of Flask, key extensions and its implementation.Ê _ Explore the Werkzeug toolkit andÊ Jinja Template engine and see how FlaskÊ interacts with JavaScript and CSS. _ Detailed modules on building and deploying RESTful applications using Flask. Ê DESCRIPTIONÊ This book teaches the reader the complete workflow of developing web applications using Python and its most outperforming microframework, Flask. The book begins with getting you up to speed in developing a strong understanding of the web application development process and how Python is used in developing the applications. You will learn how to write your own first Flask-based web application in Python. You will learn about web gateway interfaces, including CGI and WSGI along with various tools like the Jinja 2 engine, Werkzeug toolkit, and Click toolkit.Ê You will learn and practice the core features of Flask such as URL routing, rendering, handling static assets of a web application, how to handle cookies and sessions, and other HTTP objects. Once you have developed a strong knowledge of Flask, you will now dive deeper into advanced topics that includes Flask extensions for working with relational and NoSQL databases, Flask_WTF, and Flask-Bootstrap. You will explore design patterns, various blueprints on how to build modular and scalable applications, and finally how to deploy the RESTful APIs successfully on your own. WHAT YOU WILL LEARNÊÊ _ Get to know everything about the core capabilities of Flask. _ Understand the basic building blocks of Flask. _ Get familiar with advanced features of Flask, including blueprints, Flask extensions, and database connectivity. _ Get ready to design your own Flask-based web applications and RESTful APIs. _ Learn to build modular and scalable applications and how to deploy them successfully. WHO THIS BOOK IS FORÊÊÊ This book is ideal for Python enthusiasts, open source contributors, and web app developers who intend to add Python web technologies in their skillsets and startup companies. The understanding of the core Python language with intermediate level expertise is required and experience of working with SQL, HTML, CSS, and JavaScript is an added advantage. TABLE OF CONTENTS 1. Python for CGI 2. WSGI 3. Flask Fundamentals 4. URL Routing 5. Rendering Templates 6. Static Files 7. HTTP Objects 8. Using Databases 9. More Flask Extensions 10. Blueprints and Contexts 11. Web API with Flask 12. Deploying Flask Applications 13. Appendix

Building Large Language Model(LLM) Applications

Author : Anand Vemula
Publisher : Anand Vemula
ISBN 13 :
Total Pages : 77 pages
Book Rating : 4./5 ( download)

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Book Synopsis Building Large Language Model(LLM) Applications by : Anand Vemula

Download or read book Building Large Language Model(LLM) Applications written by Anand Vemula and published by Anand Vemula. This book was released on with total page 77 pages. Available in PDF, EPUB and Kindle. Book excerpt: "Building LLM Apps" is a comprehensive guide that equips readers with the knowledge and practical skills needed to develop applications utilizing large language models (LLMs). The book covers various aspects of LLM application development, starting from understanding the fundamentals of LLMs to deploying scalable and efficient solutions. Beginning with an introduction to LLMs and their importance in modern applications, the book explores the history, key concepts, and popular architectures like GPT and BERT. Readers learn how to set up their development environment, including hardware and software requirements, installing necessary tools and libraries, and leveraging cloud services for efficient development and deployment. Data preparation is essential for training LLMs, and the book provides insights into gathering and cleaning data, annotating and labeling data, and handling imbalanced data to ensure high-quality training datasets. Training large language models involves understanding training basics, best practices, distributed training techniques, and fine-tuning pre-trained models for specific tasks. Developing LLM applications requires designing user interfaces, integrating LLMs into existing systems, and building interactive features such as chatbots, text generation, sentiment analysis, named entity recognition, and machine translation. Advanced LLM techniques like prompt engineering, transfer learning, multi-task learning, and zero-shot learning are explored to enhance model capabilities. Deployment and scalability strategies are discussed to ensure smooth deployment of LLM applications while managing costs effectively. Security and ethics in LLM apps are addressed, covering bias detection, fairness, privacy, security, and ethical considerations to build responsible AI solutions. Real-world case studies illustrate the practical applications of LLMs in various domains, including customer service, healthcare, and finance. Troubleshooting and optimization techniques help readers address common issues and optimize model performance. Looking towards the future, the book highlights emerging trends and developments in LLM technology, emphasizing the importance of staying updated with advancements and adhering to ethical AI practices. "Building LLM Apps" serves as a comprehensive resource for developers, data scientists, and business professionals seeking to harness the power of large language models in their applications.

Supercharge Your Applications with GraalVM

Author : A B Vijay Kumar
Publisher : Packt Publishing Ltd
ISBN 13 : 1800566239
Total Pages : 360 pages
Book Rating : 4.8/5 (5 download)

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Book Synopsis Supercharge Your Applications with GraalVM by : A B Vijay Kumar

Download or read book Supercharge Your Applications with GraalVM written by A B Vijay Kumar and published by Packt Publishing Ltd. This book was released on 2021-08-10 with total page 360 pages. Available in PDF, EPUB and Kindle. Book excerpt: Understand the internals and architecture of GraalVM with the help of hands-on experiments and gain deep knowledge that you can apply to improve your application's performance, interoperability, and throughput. Key FeaturesGenerate faster and leaner code with minimum computing resources for high performanceCompile Java applications faster than ever to a standalone executable called native imagesCreate high-performance polyglot applications that are compatible across various JVM and non-JVM languagesBook Description GraalVM is a universal virtual machine that allows programmers to compile and run applications written in both JVM and non-JVM languages. It improves the performance and efficiency of applications, making it an ideal companion for cloud-native or microservices-based applications. This book is a hands-on guide, with step-by-step instructions on how to work with GraalVM. Starting with a quick introduction to the GraalVM architecture and how things work under the hood, you'll discover the performance benefits of running your Java applications on GraalVM. You'll then learn how to create native images and understand how AOT (ahead-of-time) can improve application performance significantly. The book covers examples of building polyglot applications that will help you explore the interoperability between languages running on the same VM. You'll also see how you can use the Truffle framework to implement any language of your choice to run optimally on GraalVM. By the end of this book, you'll not only have learned how GraalVM is beneficial in cloud-native and microservices development but also how to leverage its capabilities to create high-performing polyglot applications. What you will learnGain a solid understanding of GraalVM and how it works under the hoodWork with GraalVM's high performance optimizing compiler and see how it can be used in both JIT (just-in-time) and AOT (ahead-of-time) modesGet to grips with the various optimizations that GraalVM performs at runtimeUse advanced tools to analyze and diagnose performance issues in the codeCompile, embed, run, and interoperate between languages using Truffle on GraalVMBuild optimum microservices using popular frameworks such as Micronaut and Quarkus to create cloud-native applicationsWho this book is for This book is for JVM developers looking to optimize their application's performance. You'll also find this book useful if you're a JVM developer looking to explore options to develop polyglot applications using tools from the Python, R, Ruby, or Node.js ecosystem. A solid understanding of software development concepts and prior experience working with programming languages is necessary to get started.

The Well-Grounded Python Developer

Author : Doug Farrell
Publisher : Simon and Schuster
ISBN 13 : 1617297445
Total Pages : 294 pages
Book Rating : 4.6/5 (172 download)

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Book Synopsis The Well-Grounded Python Developer by : Doug Farrell

Download or read book The Well-Grounded Python Developer written by Doug Farrell and published by Simon and Schuster. This book was released on 2023-07-18 with total page 294 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Well-Grounded Python Developer teaches you how to write real software in Python by building on the basic language skills you already have. When you’re new to Python, it can be tough to understand where and how to use its many language features. There’s a dizzying array of libraries, and it’s challenging to fit everything together. The Well-Grounded Python Developer builds on Python skills you’ve learned in isolation and shows you how to unify them into a meaningful whole. The Well-Grounded Python Developer teaches you how to write real software in Python by building on the basic language skills you already have. It helps you see the big picture you can create out of small pieces, introducing concepts like modular construction, APIs, and the design of a basic web server. When you’re finished, you’ll have gone from having a basic understanding of Python's syntax, grammar, and libraries to using them as the tools of a professional software developer. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications.

Designing LLM Applications

Author : Anand Vemula
Publisher : Independently Published
ISBN 13 :
Total Pages : 0 pages
Book Rating : 4.3/5 (352 download)

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Book Synopsis Designing LLM Applications by : Anand Vemula

Download or read book Designing LLM Applications written by Anand Vemula and published by Independently Published. This book was released on 2024-08-07 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Designing LLM Applications: A Comprehensive Guide to Development and Deployment" provides an in-depth exploration of building and implementing applications using Large Language Models (LLMs). This guide is tailored for developers, data scientists, and AI enthusiasts aiming to harness the power of LLMs like GPT, BERT, and T5 in real-world scenarios. The book begins with a thorough introduction to LLMs, detailing their evolution, key concepts, and core technologies. It demystifies the process of setting up a development environment, from installing essential tools to running pre-trained models, offering a solid foundation for newcomers and experienced practitioners alike. In the second part, the focus shifts to designing LLM-based applications. Readers learn to identify practical use cases, define functional requirements, and address ethical and legal implications. Detailed guidance on data collection and preparation ensures high-quality inputs for model training, emphasizing the importance of data integrity. The guide then delves into advanced techniques for optimizing LLM performance, including hyperparameter tuning, reducing latency, and ensuring scalability. Strategies for deploying models, whether on cloud platforms or on-premises, are explored, alongside methods for monitoring and maintaining performance. Practical applications and case studies are central to the book. From text generation and summarization to domain-specific use cases in healthcare, finance, and education, readers gain insights into deploying LLMs effectively. The book also includes hands-on projects and tutorials, enabling readers to build and refine their own applications. Ethical considerations and best practices are addressed comprehensively, covering bias mitigation, transparency, and cost management strategies. By blending theoretical knowledge with practical guidance, "Designing LLM Applications" equips readers with the tools and expertise needed to develop sophisticated LLM applications and navigate the complexities of modern AI technologies.

Selenium WebDriver Practical Guide

Author : Satya Avasarala
Publisher :
ISBN 13 : 9781782168850
Total Pages : 0 pages
Book Rating : 4.1/5 (688 download)

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Book Synopsis Selenium WebDriver Practical Guide by : Satya Avasarala

Download or read book Selenium WebDriver Practical Guide written by Satya Avasarala and published by . This book was released on 2014 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: An easy- to- follow guide, featuring step-by-step practical tutorials to help you understand how to automate web applications for testing purposes. If you are a quality assurance / testing professional, a software developer, or a web application developer looking to create automation test scripts for your web applications, this is the perfect guide for you! As a pre-requisite, this book expects you to have a basic knowledge of Core Java, although any previous knowledge of WebDriver or Selenium-1 is not needed. By the end of this book, you will have acquired a comprehensive knowledge of WebDrive.

Optimizing Large Language Models Practical Approaches and Applications of Quantization Technique

Author : Anand Vemula
Publisher : Anand Vemula
ISBN 13 :
Total Pages : 143 pages
Book Rating : 4./5 ( download)

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Book Synopsis Optimizing Large Language Models Practical Approaches and Applications of Quantization Technique by : Anand Vemula

Download or read book Optimizing Large Language Models Practical Approaches and Applications of Quantization Technique written by Anand Vemula and published by Anand Vemula. This book was released on 2024-08-19 with total page 143 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book provides an in-depth understanding of quantization techniques and their impact on model efficiency, performance, and deployment. The book starts with a foundational overview of quantization, explaining its significance in reducing the computational and memory requirements of LLMs. It delves into various quantization methods, including uniform and non-uniform quantization, per-layer and per-channel quantization, and hybrid approaches. Each technique is examined for its applicability and trade-offs, helping readers select the best method for their specific needs. The guide further explores advanced topics such as quantization for edge devices and multi-lingual models. It contrasts dynamic and static quantization strategies and discusses emerging trends in the field. Practical examples, use cases, and case studies are provided to illustrate how these techniques are applied in real-world scenarios, including the quantization of popular models like GPT and BERT.

Hands-On LLM

Author : Anand Vemula
Publisher : Independently Published
ISBN 13 :
Total Pages : 0 pages
Book Rating : 4.3/5 (325 download)

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Book Synopsis Hands-On LLM by : Anand Vemula

Download or read book Hands-On LLM written by Anand Vemula and published by Independently Published. This book was released on 2024-07-08 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Hands-On LLM: Building Applications, Implementation, and Techniques" is a comprehensive guide that equips readers with practical skills to harness the power of Large Language Models (LLMs). The book focuses on hands-on learning, providing step-by-step instructions and real-world examples to help readers understand and apply LLMs effectively. Starting with an introduction to LLMs, the book covers their historical background, key concepts, and terminology. It explores various applications such as natural language processing, text generation, conversational AI, and more, highlighting their versatility in solving complex tasks. The core of the book delves into building and training LLMs. Readers learn how to set up their development environment, select and preprocess data, and customize model architectures like GPT and BERT. Training strategies, hyperparameter tuning, and distributed training techniques are also covered in detail. Practical projects form a significant part of the book, including text generation, sentiment analysis, named entity recognition (NER), question answering systems, and more. Each project guides readers through implementation, fine-tuning models for specific tasks, and integrating LLMs with other technologies such as knowledge graphs and computer vision. Advanced topics like model optimization, deployment strategies, and transfer learning for adapting models to new domains are discussed extensively. The book emphasizes practicality by offering insights into deploying LLMs in production environments, scaling applications, and optimizing model performance through techniques like model compression and serving methodologies. Case studies and industry-specific applications showcase success stories and lessons learned from implementing LLMs across healthcare, finance, retail, and beyond. The book concludes with an exploration of future trends in LLMs, discussing emerging research, technological advancements, and the ethical implications shaping the future of AI.