Mastering Large Language Models With Python Unleash The Power Of Advanced Natural Language Processing For Enterprise Innovation And Efficiency Using Large Language Models Llms With Python
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Mastering Large Language Models With Python
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Author : Raj Arun R
language : en
Publisher: Orange Education Pvt Ltd
Release Date : 2024-04-12
Mastering Large Language Models With Python written by Raj Arun R and has been published by Orange Education Pvt Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-04-12 with Computers categories.
A Comprehensive Guide to Leverage Generative AI in the Modern Enterprise KEY FEATURES ● Gain a comprehensive understanding of LLMs within the framework of Generative AI, from foundational concepts to advanced applications. ● Dive into practical exercises and real-world applications, accompanied by detailed code walkthroughs in Python. ● Explore LLMOps with a dedicated focus on ensuring trustworthy AI and best practices for deploying, managing, and maintaining LLMs in enterprise settings. ● Prioritize the ethical and responsible use of LLMs, with an emphasis on building models that adhere to principles of fairness, transparency, and accountability, fostering trust in AI technologies. DESCRIPTION “Mastering Large Language Models with Python” is an indispensable resource that offers a comprehensive exploration of Large Language Models (LLMs), providing the essential knowledge to leverage these transformative AI models effectively. From unraveling the intricacies of LLM architecture to practical applications like code generation and AI-driven recommendation systems, readers will gain valuable insights into implementing LLMs in diverse projects. Covering both open-source and proprietary LLMs, the book delves into foundational concepts and advanced techniques, empowering professionals to harness the full potential of these models. Detailed discussions on quantization techniques for efficient deployment, operational strategies with LLMOps, and ethical considerations ensure a well-rounded understanding of LLM implementation. Through real-world case studies, code snippets, and practical examples, readers will navigate the complexities of LLMs with confidence, paving the way for innovative solutions and organizational growth. Whether you seek to deepen your understanding, drive impactful applications, or lead AI-driven initiatives, this book equips you with the tools and insights needed to excel in the dynamic landscape of artificial intelligence. WHAT WILL YOU LEARN ● In-depth study of LLM architecture and its versatile applications across industries. ● Harness open-source and proprietary LLMs to craft innovative solutions. ● Implement LLM APIs for a wide range of tasks spanning natural language processing, audio analysis, and visual recognition. ● Optimize LLM deployment through techniques such as quantization and operational strategies like LLMOps, ensuring efficient and scalable model usage. ● Master prompt engineering techniques to fine-tune LLM outputs, enhancing quality and relevance for diverse use cases. ● Navigate the complex landscape of ethical AI development, prioritizing responsible practices to drive impactful technology adoption and advancement. WHO IS THIS BOOK FOR? This book is tailored for software engineers, data scientists, AI researchers, and technology leaders with a foundational understanding of machine learning concepts and programming. It's ideal for those looking to deepen their knowledge of Large Language Models and their practical applications in the field of AI. If you aim to explore LLMs extensively for implementing inventive solutions or spearheading AI-driven projects, this book is tailored to your needs. TABLE OF CONTENTS 1. The Basics of Large Language Models and Their Applications 2. Demystifying Open-Source Large Language Models 3. Closed-Source Large Language Models 4. LLM APIs for Various Large Language Model Tasks 5. Integrating Cohere API in Google Sheets 6. Dynamic Movie Recommendation Engine Using LLMs 7. Document-and Web-based QA Bots with Large Language Models 8. LLM Quantization Techniques and Implementation 9. Fine-tuning and Evaluation of LLMs 10. Recipes for Fine-Tuning and Evaluating LLMs 11. LLMOps - Operationalizing LLMs at Scale 12. Implementing LLMOps in Practice Using MLflow on Databricks 13. Mastering the Art of Prompt Engineering 14. Prompt Engineering Essentials and Design Patterns 15. Ethical Considerations and Regulatory Frameworks for LLMs 16. Towards Trustworthy Generative AI (A Novel Framework Inspired by Symbolic Reasoning) Index
Mastering Large Language Models With Python Unleash The Power Of Advanced Natural Language Processing For Enterprise Innovation And Efficiency Using Large Language Models Llms With Python
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Author : Raj Arun
language : en
Publisher: Orange Education Pvt Limited
Release Date : 2024-04-12
Mastering Large Language Models With Python Unleash The Power Of Advanced Natural Language Processing For Enterprise Innovation And Efficiency Using Large Language Models Llms With Python written by Raj Arun 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 2024-04-12 with Computers categories.
A Comprehensive Guide to Leverage Generative AI in the Modern Enterprise Key Features● Gain a comprehensive understanding of LLMs within the framework of Generative AI, from foundational concepts to advanced applications. ● Dive into practical exercises and real-world applications, accompanied by detailed code walkthroughs in Python. ● Explore LLMOps with a dedicated focus on ensuring trustworthy AI and best practices for deploying, managing, and maintaining LLMs in enterprise settings. Book Description “Mastering Large Language Models with Python” is an indispensable resource that offers a comprehensive exploration of Large Language Models (LLMs), providing the essential knowledge to leverage these transformative AI models effectively. From unraveling the intricacies of LLM architecture to practical applications like code generation and AI-driven recommendation systems, readers will gain valuable insights into implementing LLMs in diverse projects. Covering both open-source and proprietary LLMs, the book delves into foundational concepts and advanced techniques, empowering professionals to harness the full potential of these models. Detailed discussions on quantization techniques for efficient deployment, operational strategies with LLMOps, and ethical considerations ensure a well-rounded understanding of LLM implementation. Through real-world case studies, code snippets, and practical examples, readers will navigate the complexities of LLMs with confidence, paving the way for innovative solutions and organizational growth. Whether you seek to deepen your understanding, drive impactful applications, or lead AI-driven initiatives, this book equips you with the tools and insights needed to excel in the dynamic landscape of artificial intelligence. What you will learn ● In-depth study of LLM architecture and its versatile applications across industries. ● Harness open-source and proprietary LLMs to craft innovative solutions. ● Implement LLM APIs for a wide range of tasks spanning natural language processing, audio analysis, and visual recognition. ● Optimize LLM deployment through techniques such as quantization and operational strategies like LLMOps, ensuring efficient and scalable model usage. Table of Contents 1. The Basics of Large Language Models and Their Applications 2. Demystifying Open-Source Large Language Models 3. Closed-Source Large Language Models 4. LLM APIs for Various Large Language Model Tasks 5. Integrating Cohere API in Google Sheets 6. Dynamic Movie Recommendation Engine Using LLMs 7. Document-and Web-based QA Bots with Large Language Models 8. LLM Quantization Techniques and Implementation 9. Fine-tuning and Evaluation of LLMs 10. Recipes for Fine-Tuning and Evaluating LLMs 11. LLMOps - Operationalizing LLMs at Scale 12. Implementing LLMOps in Practice Using MLflow on Databricks 13. Mastering the Art of Prompt Engineering 14. Prompt Engineering Essentials and Design Patterns 15. Ethical Considerations and Regulatory Frameworks for LLMs 16. Towards Trustworthy Generative AI (A Novel Framework Inspired by Symbolic Reasoning) Index
Agile Machine Learning
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Author : Eric Carter
language : en
Publisher: Apress
Release Date : 2019-08-21
Agile Machine Learning written by Eric Carter and has been published by Apress this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-08-21 with Computers categories.
Build resilient applied machine learning teams that deliver better data products through adapting the guiding principles of the Agile Manifesto. Bringing together talented people to create a great applied machine learning team is no small feat. With developers and data scientists both contributing expertise in their respective fields, communication alone can be a challenge. Agile Machine Learning teaches you how to deliver superior data products through agile processes and to learn, by example, how to organize and manage a fast-paced team challenged with solving novel data problems at scale, in a production environment. The authors’ approach models the ground-breaking engineering principles described in the Agile Manifesto. The book provides further context, and contrasts the original principles with the requirements of systems that deliver a data product. What You'll Learn Effectively run a data engineeringteam that is metrics-focused, experiment-focused, and data-focused Make sound implementation and model exploration decisions based on the data and the metrics Know the importance of data wallowing: analyzing data in real time in a group setting Recognize the value of always being able to measure your current state objectively Understand data literacy, a key attribute of a reliable data engineer, from definitions to expectations Who This Book Is For Anyone who manages a machine learning team, or is responsible for creating production-ready inference components. Anyone responsible for data project workflow of sampling data; labeling, training, testing, improving, and maintaining models; and system and data metrics will also find this book useful. Readers should be familiar with software engineering and understand the basics of machine learning and working with data.
Cognitive Virtual Assistants Using Google Dialogflow
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Author : Navin Sabharwal
language : en
Publisher: Apress
Release Date : 2020-03-16
Cognitive Virtual Assistants Using Google Dialogflow written by Navin Sabharwal and has been published by Apress this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-03-16 with Computers categories.
Follow a step-by-step, hands-on approach to building production-ready enterprise cognitive virtual assistants using Google Dialogflow. This book provides an overview of the various cognitive technology choices available and takes a deep dive into cognitive virtual agents for handling complex real-life use cases in various industries such as travel and weather. You’ll delve deeper into the advanced features of cognitive virtual assistants implementing features such as input/output context, follow-up intents, actions and parameters, and handling complex multiple intents. You’ll learn how to integrate with third-party messaging platforms by integrating your cognitive bot with Facebook messenger. You’ll also integrate with third-party APIs to enrich your cognitive bots using webhooks. Cognitive Virtual Assistants Using Google Dialogflow takes the complexity out of the cognitive platform and provides rich guidance which you can use when developing your owncognitive bots. The book covers Google Dialogflow in-depth and starts with the basics, serving as a hands-on guide for developers who are starting out on their journey with Google Dialogflow. All the code presented in the book will be available in the form of scripts and configuration files, which allows you to try out the examples and extend them in interesting ways. What You Will Learn Develop cognitive bots with Google Dialogflow technology Use advanced features to handle complex conversation scenarios Enrich the bot’s conversations by understanding the sentiment of the user See best practices for developing cognitive bots Enhance a cognitive bot by integrating with third-party services Who This Book Is For AI and ML developers.
C Programming Cookbook
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Author : B. M. Harwani
language : en
Publisher:
Release Date : 2019-03-29
C Programming Cookbook written by B. M. Harwani and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-03-29 with Computers categories.
A comprehensive guide with curated recipes to help you gain a deeper understanding of modern C. Key Features Learn how to make your applications swift and robust by leveraging powerful features of C Understand the workings of arrays, strings, functions, and more down to how they operate in memory Master process synchronization during multi-tasking and server-client process communication Book Description C is a high-level language that's popular among developers. It enables you to write drivers for different devices, access machine-level hardware, apply dynamic memory allocation, and much more. With self-contained tutorials, known as recipes, this book will guide you in dealing with C and its idiosyncrasies and help you benefit from its latest features. Beginning with common tasks, each recipe addresses a specific problem followed by explaining the solution to get you acquainted with what goes on under the hood. You will explore core concepts of the programming language, including how to work with strings, pointers, and single and multi-dimensional arrays. You will also learn how to break a large application into small modules by creating functions, handling files, and using a database. Finally, the book will take you through advanced concepts such as concurrency and interprocess communication. By the end of this book, you'll have a clear understanding and deeper knowledge of C programming, which will help you become a better developer. What you will learn Manipulate single and multi-dimensional arrays Perform complex operations on strings Understand how to use pointers and memory optimally Discover how to use arrays, functions, and strings to make large applications Implement multitasking using threads and process synchronization Establish communication between two or more processes using different techniques Store simple text in files and store data in a database Who this book is for If you're a programmer with basic experience in C and want to leverage its features through modern programming practices, then this book is for you.
Hands On Continuous Integration And Delivery
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Author : Jean-Marcel Belmont
language : en
Publisher: Packt Publishing Ltd
Release Date : 2018-08-29
Hands On Continuous Integration And Delivery written by Jean-Marcel Belmont 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 2018-08-29 with Computers categories.
Understand various tools and practices for building a continuous integration and delivery pipeline effectively Key Features Get up and running with the patterns of continuous integration Learn Jenkins UI for developing plugins and build an effective Jenkins pipeline Automate CI/CD with command-line tools and scripts Book Description Hands-On Continuous Integration and Delivery starts with the fundamentals of continuous integration (CI) and continuous delivery (CD) and where it fits in the DevOps ecosystem. You will explore the importance of stakeholder collaboration as part of CI/CD. As you make your way through the chapters, you will get to grips with Jenkins UI, and learn to install Jenkins on different platforms, add plugins, and write freestyle scripts. Next, you will gain hands-on experience of developing plugins with Jenkins UI, building the Jenkins 2.0 pipeline, and performing Docker integration. In the concluding chapters, you will install Travis CI and Circle CI and carry out scripting, logging, and debugging, helping you to acquire a broad knowledge of CI/CD with Travis CI and CircleCI. By the end of this book, you will have a detailed understanding of best practices for CI/CD systems and be able to implement them with confidence. What you will learn Install Jenkins on multiple operating systems Work with Jenkins freestyle scripts, pipeline syntax, and methodology Explore Travis CI build life cycle events and multiple build languages Master the Travis CI CLI (command-line interface) and automate tasks with the CLI Use CircleCI CLI jobs and work with pipelines Automate tasks using CircleCI CLI and learn to debug and troubleshoot Learn open source tooling such as Git and GitHub Install Docker and learn concepts in shell scripting Who this book is for Hands-On Continuous Integration and Delivery is for system administrators, DevOps engineers, and build and release engineers who want to understand the concept of CI and gain hands-on experience working with prominent tools in the CI ecosystem. Basic knowledge of software delivery is an added advantage.
Vfx Fundamentals
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Author : Wallace Jackson
language : en
Publisher: Apress
Release Date : 2016-08-12
Vfx Fundamentals written by Wallace Jackson and has been published by Apress this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-08-12 with Computers categories.
Learn concepts central to visual special effects using the free Black Magic Design Fusion 8.0 software package. This book also provides foundational background information regarding concepts central to digital image compositing, digital video editing, digital illustration, digital painting, 3D, and digital audio in the first six chapters on new media theory, concepts and terminology. This book builds on the foundational concepts of digital image compositing, digital audio, digital video, digital illustration and digital painting. VFX Fundamentals introduces more advanced VFX concepts and pipelines as the chapters progress, covering topics such as flow node compositing, timeline animation, animated polyline masking, bluescreen and greenscreen matte pulling (generation), using Primatte and Fusion 8 Ultra Keyer, motion tracking, 3D rendering and compositing, auxiliary channels, and particle systems and particle physics dynamics, among other topics. “br>What You'll Learn See the new media components (raster, vector, audio, video, rendering) needed for VFX Discover the concepts behind the VFX content production workflow Install and utilize Black Magic Design Fusion 8 and its Visual Programming Language Master the concepts behind resolution, aspect ratio, bit-rate, color depth, layers, alpha, and masking Work with 2D VFX concepts such as animated masking, matte pulling (Primatte V) and motion tracking Harness 3D VFX concepts such as 3D geometry, materials, lighting, animation and auxiliary channels Use advanced VFX concepts such as particle systems animation using real-world physics (forces) Who This Book Is Fordiv SFX artists, VFX artists, video editors, website developers, filmmakers, 2D and 3D animators, digital signage producers, e-learning content creators, game developers, multimedia producers.
Practical React Native
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Author : Frank Zammetti
language : en
Publisher: Apress
Release Date : 2018-11-12
Practical React Native written by Frank Zammetti and has been published by Apress this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-11-12 with Computers categories.
Discover how to use React Native in the real world, from scratch. This book shows you what React Native has to offer, where it came from, and where it’s going. You'll begin with a solid foundation of practical knowledge, and then build on it immediately by constructing three different apps. You'll learn how to use each feature of React Native by working on two full projects and one full game. These aren’t just simple React Native Hello World examples (although you’ll naturally start there!) but are apps that you can, if you so choose, install on your mobile devices and use for real. Throughout this book, you'll gain real-world familiarity with React Native as well as supporting components from Expo, NativeBase, React Navigation and the Redux and Lodash libraries. You'll also build server-side code for a mobile React Native app to talk to using the popular Node.js and Socket.io library, providing you a holistic view of thingseven beyond React Native. And, you'll see many helpful tips, tricks and gotchas to watch out for along the way! Practical React Native offers practical exercises that will give you a solid grasp of building apps with React Native, allowing you to springboard into creating more advanced apps on your own.Creating a game with React Native will allow you to see a whole other perspective on what React Native can do. What You'll Learn Master the basics of React Native Create a logically structured project Review interface elements, such as widgets, controls, and extensions Build layouts Work with Expo, an open source toolchain Who This book Is For The primary audience is mobile developers and anyone looking to build for multiple mobile platforms and trying to do so with a codebase that is largely the same across all. Readers will need a decent foundation, but not necessarily be experts in, HTML, CSS, and JavaScript, but I'll assume little beyond that.
Machine Learning For Cybersecurity Cookbook
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Author : Emmanuel Tsukerman
language : en
Publisher: Packt Publishing Ltd
Release Date : 2019-11-25
Machine Learning For Cybersecurity Cookbook written by Emmanuel Tsukerman 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 2019-11-25 with Computers categories.
Learn how to apply modern AI to create powerful cybersecurity solutions for malware, pentesting, social engineering, data privacy, and intrusion detection Key FeaturesManage data of varying complexity to protect your system using the Python ecosystemApply ML to pentesting, malware, data privacy, intrusion detection system(IDS) and social engineeringAutomate your daily workflow by addressing various security challenges using the recipes covered in the bookBook Description Organizations today face a major threat in terms of cybersecurity, from malicious URLs to credential reuse, and having robust security systems can make all the difference. With this book, you'll learn how to use Python libraries such as TensorFlow and scikit-learn to implement the latest artificial intelligence (AI) techniques and handle challenges faced by cybersecurity researchers. You'll begin by exploring various machine learning (ML) techniques and tips for setting up a secure lab environment. Next, you'll implement key ML algorithms such as clustering, gradient boosting, random forest, and XGBoost. The book will guide you through constructing classifiers and features for malware, which you'll train and test on real samples. As you progress, you'll build self-learning, reliant systems to handle cybersecurity tasks such as identifying malicious URLs, spam email detection, intrusion detection, network protection, and tracking user and process behavior. Later, you'll apply generative adversarial networks (GANs) and autoencoders to advanced security tasks. Finally, you'll delve into secure and private AI to protect the privacy rights of consumers using your ML models. By the end of this book, you'll have the skills you need to tackle real-world problems faced in the cybersecurity domain using a recipe-based approach. What you will learnLearn how to build malware classifiers to detect suspicious activitiesApply ML to generate custom malware to pentest your securityUse ML algorithms with complex datasets to implement cybersecurity conceptsCreate neural networks to identify fake videos and imagesSecure your organization from one of the most popular threats – insider threatsDefend against zero-day threats by constructing an anomaly detection systemDetect web vulnerabilities effectively by combining Metasploit and MLUnderstand how to train a model without exposing the training dataWho this book is for This book is for cybersecurity professionals and security researchers who are looking to implement the latest machine learning techniques to boost computer security, and gain insights into securing an organization using red and blue team ML. This recipe-based book will also be useful for data scientists and machine learning developers who want to experiment with smart techniques in the cybersecurity domain. Working knowledge of Python programming and familiarity with cybersecurity fundamentals will help you get the most out of this book.
Practical Ansible 2
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Author : Daniel Oh
language : en
Publisher: Packt Publishing Ltd
Release Date : 2020-06-05
Practical Ansible 2 written by Daniel Oh 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 2020-06-05 with Computers categories.
Leverage the power of Ansible to gain complete control over your systems and automate application deployment Key FeaturesUse Ansible 2.9 to automate and control your infrastructureDelve into advanced functionality such as plugins and custom modules in AnsibleAutomate and orchestrate major cloud platforms such as OpenStack, AWS, and Azure using AnsibleBook Description Ansible enables you to automate software provisioning, configuration management, and application roll-outs, and can be used as a deployment and orchestration tool. While Ansible provides simple yet powerful features to automate multi-layer environments using agentless communication, it can also solve other critical IT challenges, such as ensuring continuous integration and continuous deployment (CI/CD) with zero downtime. In this book, you'll work with Ansible 2.9 and learn to solve complex issues quickly with the help of task-oriented scenarios. You'll start by installing and configuring Ansible on Linux and macOS to automate monotonous and repetitive IT tasks and get to grips with concepts such as playbooks, inventories, and network modules. As you progress, you'll gain insight into the YAML syntax and learn how to port between Ansible versions. In addition to this, you'll also understand how Ansible enables you to orchestrate multi-layer environments such as networks, containers, and the cloud. By the end of this Ansible book, you'll be well - versed in writing playbooks and other related Ansible code to overcome just about all of your IT challenges, from infrastructure-as-code provisioning to application deployments, and even handling the mundane day-to-day maintenance tasks that take up so much valuable time. What you will learnBecome familiar with the fundamentals of the Ansible frameworkSet up role-based variables and dependenciesAvoid common mistakes and pitfalls when writing automation code in AnsibleExtend Ansible by developing your own modules and pluginsContribute to the Ansible project by submitting your own codeFollow best practices for working with cloud environment inventoriesTroubleshoot issues triggered during Ansible playbook runsWho this book is for If you are a DevOps engineer, administrator, or any IT professional looking to automate IT tasks using Ansible, this book is for you. Prior knowledge of Ansible is not necessary.