Download or read book OpenAI API Cookbook written by Henry Habib and published by Packt Publishing Ltd. This book was released on 2024-03-12 with total page 192 pages. Available in PDF, EPUB and Kindle. Book excerpt: Explore the vast possibilities of integrating the ChatGPT API across various domains, from creating simple wrappers to developing knowledge-based assistants, multi-model applications, and conversational interfaces Key Features Understand the different elements, endpoints, and parameters of the OpenAI API Build tailored intelligent applications and workflows with the OpenAI API Create versatile assistants with for a multitude of tasks Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionAs artificial intelligence continues to reshape industries with OpenAI at the forefront of AI research, knowing how to create innovative applications such as chatbots, virtual assistants, content generators, and productivity enhancers is a game-changer. This book takes a practical, recipe-based approach to unlocking the power of OpenAI API to build high-performance intelligent applications in diverse industries and seamlessly integrate ChatGPT in your workflows to increase productivity. You’ll begin with the OpenAI API fundamentals, covering setup, authentication, and key parameters, and quickly progress to the different elements of the OpenAI API. Once you’ve learned how to use it effectively and tweak parameters for better results, you’ll follow advanced recipes for enhancing user experience and refining outputs. The book guides your transition from development to live application deployment, setting up the API for public use and application backend. Further, you’ll discover step-by-step recipes for building knowledge-based assistants and multi-model applications tailored to your specific needs. By the end of this book, you’ll have worked through recipes involving various OpenAI API endpoints and built a variety of intelligent applications, ready to apply this experience to building AI-powered solutions of your own.What you will learn Grasp the fundamentals of the OpenAI API Navigate the API's capabilities and limitations of the API Set up the OpenAI API with step-by-step instructions, from obtaining your API key to making your first call Explore advanced features such as system messages, fine-tuning, and the effects of different parameters Integrate the OpenAI API into existing applications and workflows to enhance their functionality with AI Design and build applications that fully harness the power of ChatGPT Who this book is for This book is perfect for developers, data scientists, AI/tech enthusiasts, citizen developers, and no-code aficionados keen on using and mastering the OpenAI API. Whether you’re a beginner or experienced professional, this book is ideal for quickly creating intelligent applications such as chatbots or content generators, through step-by-step recipes that take you from the basics of the API to creating sophisticated applications systematically. The OpenAI API is accessed with Python in this book, so familiarity with Python and APIs is preferred but not mandatory.

Download or read book ChatGPT for Cybersecurity Cookbook written by Clint Bodungen and published by Packt Publishing Ltd. This book was released on 2024-03-29 with total page 372 pages. Available in PDF, EPUB and Kindle. Book excerpt: Master ChatGPT and the OpenAI API and harness the power of cutting-edge generative AI and large language models to revolutionize the way you perform penetration testing, threat detection, and risk assessment. Key Features Enhance your skills by leveraging ChatGPT to generate complex commands, write code, and create tools Automate penetration testing, risk assessment, and threat detection tasks using the OpenAI API and Python programming Revolutionize your approach to cybersecurity with an AI-powered toolkit Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionAre you ready to unleash the potential of AI-driven cybersecurity? This cookbook takes you on a journey toward enhancing your cybersecurity skills, whether you’re a novice or a seasoned professional. By leveraging cutting-edge generative AI and large language models such as ChatGPT, you'll gain a competitive advantage in the ever-evolving cybersecurity landscape. ChatGPT for Cybersecurity Cookbook shows you how to automate and optimize various cybersecurity tasks, including penetration testing, vulnerability assessments, risk assessment, and threat detection. Each recipe demonstrates step by step how to utilize ChatGPT and the OpenAI API to generate complex commands, write code, and even create complete tools. You’ll discover how AI-powered cybersecurity can revolutionize your approach to security, providing you with new strategies and techniques for tackling challenges. As you progress, you’ll dive into detailed recipes covering attack vector automation, vulnerability scanning, GPT-assisted code analysis, and more. By learning to harness the power of generative AI, you'll not only expand your skillset but also increase your efficiency. By the end of this cybersecurity book, you’ll have the confidence and knowledge you need to stay ahead of the curve, mastering the latest generative AI tools and techniques in cybersecurity.What you will learn Master ChatGPT prompt engineering for complex cybersecurity tasks Use the OpenAI API to enhance and automate penetration testing Implement artificial intelligence-driven vulnerability assessments and risk analyses Automate threat detection with the OpenAI API Develop custom AI-enhanced cybersecurity tools and scripts Perform AI-powered cybersecurity training and exercises Optimize cybersecurity workflows using generative AI-powered techniques Who this book is for This book is for cybersecurity professionals, IT experts, and enthusiasts looking to harness the power of ChatGPT and the OpenAI API in their cybersecurity operations. Whether you're a red teamer, blue teamer, or security researcher, this book will help you revolutionize your approach to cybersecurity with generative AI-powered techniques. A basic understanding of cybersecurity concepts along with familiarity in Python programming is expected. Experience with command-line tools and basic knowledge of networking concepts and web technologies is also required.

Download or read book Building AI Applications with OpenAI APIs written by Martin Yanev and published by Packt Publishing Ltd. This book was released on 2024-10-04 with total page 252 pages. Available in PDF, EPUB and Kindle. Book excerpt: Improve your app development skills by building a ChatGPT clone, code bug fixer, quiz generator, translation app, email auto-reply, PowerPoint generator, and more Key Features Transition into an expert AI developer by mastering ChatGPT concepts, including fine-tuning and integrations Gain hands-on experience through real-world projects covering a wide range of AI applications Implement payment systems in your applications by integrating the ChatGPT API with Stripe Purchase of the print or Kindle book includes a free PDF eBook Book Description Unlock the power of AI in your applications with ChatGPT with this practical guide that shows you how to seamlessly integrate OpenAI APIs into your projects, enabling you to navigate complex APIs and ensure seamless functionality with ease. This new edition is updated with key topics such as OpenAI Embeddings, which’ll help you understand the semantic relationships between words and phrases. You’ll find out how to use ChatGPT, Whisper, and DALL-E APIs through 10 AI projects using the latest OpenAI models, GPT-3.5, and GPT-4, with Visual Studio Code as the IDE. Within these projects, you’ll integrate ChatGPT with frameworks and tools such as Flask, Django, Microsoft Office APIs, and PyQt. You’ll get to grips with NLP tasks, build a ChatGPT clone, and create an AI code bug-fixing SaaS app. The chapters will also take you through speech recognition, text-to-speech capabilities, language translation, generating email replies, creating PowerPoint presentations, and fine-tuning ChatGPT, along with adding payment methods by integrating the ChatGPT API with Stripe. By the end of this book, you’ll be able to develop, deploy, and monetize your own groundbreaking applications by harnessing the full potential of ChatGPT APIs. What you will learn Develop a solid foundation in using the OpenAI API for NLP tasks Build, deploy, and integrate payments into various desktop and SaaS AI applications Integrate ChatGPT with frameworks such as Flask, Django, and Microsoft Office APIs Unleash your creativity by integrating DALL-E APIs to generate stunning AI art within your desktop apps Experience the power of Whisper API's speech recognition and text-to-speech features Find out how to fine-tune ChatGPT models for your specific use case Master AI embeddings to measure the relatedness of text strings Who this book is for This book is for a diverse range of professionals, including programmers, entrepreneurs, and software enthusiasts. Beginner programmers, Python developers exploring AI applications with ChatGPT, software developers integrating AI technology, and web developers creating AI-powered web applications with ChatGPT will find this book beneficial. Scholars and researchers working on AI projects with ChatGPT will also find it valuable. Basic knowledge of Python and familiarity with APIs is needed to understand the topics covered in this book.

Download or read book The Regularization Cookbook written by Vincent Vandenbussche and published by Packt Publishing Ltd. This book was released on 2023-07-31 with total page 424 pages. Available in PDF, EPUB and Kindle. Book excerpt: Methodologies and recipes to regularize any machine learning and deep learning model using cutting-edge technologies such as stable diffusion, Dall-E and GPT-3 Purchase of the print or Kindle book includes a free PDF eBook Key Features Learn to diagnose the need for regularization in any machine learning model Regularize different ML models using a variety of techniques and methods Enhance the functionality of your models using state of the art computer vision and NLP techniques Book Description Regularization is an infallible way to produce accurate results with unseen data, however, applying regularization is challenging as it is available in multiple forms and applying the appropriate technique to every model is a must. The Regularization Cookbook provides you with the appropriate tools and methods to handle any case, with ready-to-use working codes as well as theoretical explanations. After an introduction to regularization and methods to diagnose when to use it, you'll start implementing regularization techniques on linear models, such as linear and logistic regression, and tree-based models, such as random forest and gradient boosting. You'll then be introduced to specific regularization methods based on data, high cardinality features, and imbalanced datasets. In the last five chapters, you'll discover regularization for deep learning models. After reviewing general methods that apply to any type of neural network, you'll dive into more NLP-specific methods for RNNs and transformers, as well as using BERT or GPT-3. By the end, you'll explore regularization for computer vision, covering CNN specifics, along with the use of generative models such as stable diffusion and Dall-E. By the end of this book, you'll be armed with different regularization techniques to apply to your ML and DL models. What you will learn Diagnose overfitting and the need for regularization Regularize common linear models such as logistic regression Understand regularizing tree-based models such as XGBoos Uncover the secrets of structured data to regularize ML models Explore general techniques to regularize deep learning models Discover specific regularization techniques for NLP problems using transformers Understand the regularization in computer vision models and CNN architectures Apply cutting-edge computer vision regularization with generative models Who this book is for This book is for data scientists, machine learning engineers, and machine learning enthusiasts, looking to get hands-on knowledge to improve the performances of their models. Basic knowledge of Python is a prerequisite.

Download or read book Python Natural Language Processing Cookbook written by Zhenya Antić and published by Packt Publishing Ltd. This book was released on 2024-09-13 with total page 312 pages. Available in PDF, EPUB and Kindle. Book excerpt: Updated to include three new chapters on transformers, natural language understanding (NLU) with explainable AI, and dabbling with popular LLMs from Hugging Face and OpenAI Key Features Leverage ready-to-use recipes with the latest LLMs, including Mistral, Llama, and OpenAI models Use LLM-powered agents for custom tasks and real-world interactions Gain practical, in-depth knowledge of transformers and their role in implementing various NLP tasks with open-source and advanced LLMs Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionHarness the power of Natural Language Processing to overcome real-world text analysis challenges with this recipe-based roadmap written by two seasoned NLP experts with vast experience transforming various industries with their NLP prowess. You’ll be able to make the most of the latest NLP advancements, including large language models (LLMs), and leverage their capabilities through Hugging Face transformers. Through a series of hands-on recipes, you’ll master essential techniques such as extracting entities and visualizing text data. The authors will expertly guide you through building pipelines for sentiment analysis, topic modeling, and question-answering using popular libraries like spaCy, Gensim, and NLTK. You’ll also learn to implement RAG pipelines to draw out precise answers from a text corpus using LLMs. This second edition expands your skillset with new chapters on cutting-edge LLMs like GPT-4, Natural Language Understanding (NLU), and Explainable AI (XAI)—fostering trust and transparency in your NLP models. By the end of this book, you'll be equipped with the skills to apply advanced text processing techniques, use pre-trained transformer models, build custom NLP pipelines to extract valuable insights from text data to drive informed decision-making.What you will learn Understand fundamental NLP concepts along with their applications using examples in Python Classify text quickly and accurately with rule-based and supervised methods Train NER models and perform sentiment analysis to identify entities and emotions in text Explore topic modeling and text visualization to reveal themes and relationships within text Leverage Hugging Face and OpenAI LLMs to perform advanced NLP tasks Use question-answering techniques to handle both open and closed domains Apply XAI techniques to better understand your model predictions Who this book is for This updated edition of the Python Natural Language Processing Cookbook is for data scientists, machine learning engineers, and developers with a background in Python. Whether you’re looking to learn NLP techniques, extract valuable insights from textual data, or create foundational applications, this book will equip you with basic to intermediate skills. No prior NLP knowledge is necessary to get started. All you need is familiarity with basic programming principles. For seasoned developers, the updated sections offer the latest on transformers, explainable AI, and Generative AI with LLMs.

Download or read book Mastering NLP from Foundations to LLMs written by Lior Gazit and published by Packt Publishing Ltd. This book was released on 2024-04-26 with total page 340 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book The Midjourney Expedition written by Margarida Barreto and published by Packt Publishing Ltd. This book was released on 2024-04-30 with total page 326 pages. Available in PDF, EPUB and Kindle. Book excerpt: Harness the power of Midjourney to create impactful and memorable artistic outputs and gain a distinctive edge in your professional endeavors Key Features Master Midjourney prompting with the help of practical examples from an experienced communication and web design specialist Explore Midjourney's capabilities to create visually stunning art without prior design knowledge Gain practical insights into how to strategically apply AI-generated art in your work Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionLike various other fields, AI offers boundless possibilities when it comes to art. Midjourney is one of the leading AI art creation tools that can assist you in your artistic ideas, regardless of your technical skill level. Written by an accomplished communication and web design specialist, The Midjourney Expedition is your guide to harnessing the power of AI in your creative journey. With this guide, you’ll explore the extensive features of Midjourney and start creating compelling AI-generated art with ease. The first set of chapters will teach you how to set up and use Discord for personalized and seamless art creation, with a dedicated section that will help you understand the different versions of Midjourney and their capabilities. As you progress, you’ll hone your prompt engineering skills, and eventually learn how to leverage the power of complex prompts. You’ll also learn how Midjourney-generated images can be integrated into a multitude of workflows and domains through real-life case studies. In the last set of chapters, you’ll get to grips with real-world applications of Midjourney for storytelling, creating moodboards, and more. By the end of this book, you’ll not only be proficient in using Midjourney, but also understand how to strategically apply AI-generated art in your projects.What you will learn Navigate and master Midjourney's extensive features for AI art creation Apply practical techniques to create visually stunning AI-generated artwork Accelerate your creative process to produce captivating visual content Understand and master essential parameters to enhance your creations Create consistent characters for storytelling Incorporate AI-generated art into various work contexts Who this book is for The Midjourney Expedition is for creative individuals who are looking to visually express their ideas through the power of AI. While this book will certainly benefit designers, it's equally valuable for marketing professionals, brand strategists, content creators, media managers, and entrepreneurs. Those responsible for creating compelling visual content to represent a brand, product, or concept will also find this book useful. Basic knowledge of web user interfaces will be helpful, but not required.

Download or read book Building AI Applications with Microsoft Semantic Kernel written by Lucas A. Meyer and published by Packt Publishing Ltd. This book was released on 2024-06-21 with total page 252 pages. Available in PDF, EPUB and Kindle. Book excerpt: Unlock the power of GenAI by effortlessly linking your C# and Python apps with cutting-edge models, orchestrating diverse AI services with finesse, and crafting bespoke applications through immersive, real-world examples Key Features Link your C# and Python applications with the latest AI models from OpenAI Combine and orchestrate different AI services such as text and image generators Create your own AI apps with real-world use case examples that show you how to use basic generative AI, create images, process documents, use a vector database Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionIn the fast-paced world of AI, developers are constantly seeking efficient ways to integrate AI capabilities into their apps. Microsoft Semantic Kernel simplifies this process by using the GenAI features from Microsoft and OpenAI. Written by Lucas A. Meyer, a Principal Research Scientist in Microsoft’s AI for Good Lab, this book helps you get hands on with Semantic Kernel. It begins by introducing you to different generative AI services such as GPT-3.5 and GPT-4, demonstrating their integration with Semantic Kernel. You’ll then learn to craft prompt templates for reuse across various AI services and variables. Next, you’ll learn how to add functionality to Semantic Kernel by creating your own plugins. The second part of the book shows you how to combine multiple plugins to execute complex actions, and how to let Semantic Kernel use its own AI to solve complex problems by calling plugins, including the ones made by you. The book concludes by teaching you how to use vector databases to expand the memory of your AI services and how to help AI remember the context of earlier requests. You’ll also be guided through several real-world examples of applications, such as RAG and custom GPT agents. By the end of this book, you'll have gained the knowledge you need to start using Semantic Kernel to add AI capabilities to your applications.What you will learn Write reusable AI prompts and connect to different AI providers Create new plugins that extend the capabilities of AI services Understand how to combine multiple plugins to execute complex actions Orchestrate multiple AI services to accomplish a task Leverage the powerful planner to automatically create appropriate AI calls Use vector databases as additional memory for your AI tasks Deploy your application to ChatGPT, making it available to hundreds of millions of users Who this book is for This book is for beginner-level to experienced .NET or Python software developers who want to quickly incorporate the latest AI technologies into their applications, without having to learn the details of every new AI service. Product managers with some development experience will find this book helpful while creating proof-of-concept applications. This book requires working knowledge of programming basics.

Download or read book Learn OpenAI Whisper written by Josué R. Batista and published by Packt Publishing Ltd. This book was released on 2024-05-31 with total page 372 pages. Available in PDF, EPUB and Kindle. Book excerpt: Master automatic speech recognition (ASR) with groundbreaking generative AI for unrivaled accuracy and versatility in audio processing Key Features Uncover the intricate architecture and mechanics behind Whisper's robust speech recognition Apply Whisper's technology in innovative projects, from audio transcription to voice synthesis Navigate the practical use of Whisper in real-world scenarios for achieving dynamic tech solutions Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionAs the field of generative AI evolves, so does the demand for intelligent systems that can understand human speech. Navigating the complexities of automatic speech recognition (ASR) technology is a significant challenge for many professionals. This book offers a comprehensive solution that guides you through OpenAI's advanced ASR system. You’ll begin your journey with Whisper's foundational concepts, gradually progressing to its sophisticated functionalities. Next, you’ll explore the transformer model, understand its multilingual capabilities, and grasp training techniques using weak supervision. The book helps you customize Whisper for different contexts and optimize its performance for specific needs. You’ll also focus on the vast potential of Whisper in real-world scenarios, including its transcription services, voice-based search, and the ability to enhance customer engagement. Advanced chapters delve into voice synthesis and diarization while addressing ethical considerations. By the end of this book, you'll have an understanding of ASR technology and have the skills to implement Whisper. Moreover, Python coding examples will equip you to apply ASR technologies in your projects as well as prepare you to tackle challenges and seize opportunities in the rapidly evolving world of voice recognition and processing.What you will learn Integrate Whisper into voice assistants and chatbots Use Whisper for efficient, accurate transcription services Understand Whisper's transformer model structure and nuances Fine-tune Whisper for specific language requirements globally Implement Whisper in real-time translation scenarios Explore voice synthesis capabilities using Whisper's robust tech Execute voice diarization with Whisper and NVIDIA's NeMo Navigate ethical considerations in advanced voice technology Who this book is for Learn OpenAI Whisper is designed for a diverse audience, including AI engineers, tech professionals, and students. It's ideal for those with a basic understanding of machine learning and Python programming, and an interest in voice technology, from developers integrating ASR in applications to researchers exploring the cutting-edge possibilities in artificial intelligence.

Download or read book Essential Guide to LLMOps written by RYAN. DOAN and published by Packt Publishing Ltd. This book was released on 2024-07-31 with total page 190 pages. Available in PDF, EPUB and Kindle. Book excerpt: Unlock the secrets to mastering LLMOps with innovative approaches to streamline AI workflows, improve model efficiency, and ensure robust scalability, revolutionizing your language model operations from start to finish Key Features Gain a comprehensive understanding of LLMOps, from data handling to model governance Leverage tools for efficient LLM lifecycle management, from development to maintenance Discover real-world examples of industry cutting-edge trends in generative AI operation Purchase of the print or Kindle book includes a free PDF eBook Book Description The rapid advancements in large language models (LLMs) bring significant challenges in deployment, maintenance, and scalability. This Essential Guide to LLMOps provides practical solutions and strategies to overcome these challenges, ensuring seamless integration and the optimization of LLMs in real-world applications. This book takes you through the historical background, core concepts, and essential tools for data analysis, model development, deployment, maintenance, and governance. You’ll learn how to streamline workflows, enhance efficiency in LLMOps processes, employ LLMOps tools for precise model fine-tuning, and address the critical aspects of model review and governance. You’ll also get to grips with the practices and performance considerations that are necessary for the responsible development and deployment of LLMs. The book equips you with insights into model inference, scalability, and continuous improvement, and shows you how to implement these in real-world applications. By the end of this book, you’ll have learned the nuances of LLMOps, including effective deployment strategies, scalability solutions, and continuous improvement techniques, equipping you to stay ahead in the dynamic world of AI. What you will learn Understand the evolution and impact of LLMs in AI Differentiate between LLMOps and traditional MLOps Utilize LLMOps tools for data analysis, preparation, and fine-tuning Master strategies for model development, deployment, and improvement Implement techniques for model inference, serving, and scalability Integrate human-in-the-loop strategies for refining LLM outputs Grasp the forefront of emerging technologies and practices in LLMOps Who this book is for This book is for machine learning professionals, data scientists, ML engineers, and AI leaders interested in LLMOps. It is particularly valuable for those developing, deploying, and managing LLMs, as well as academics and students looking to deepen their understanding of the latest AI and machine learning trends. Professionals in tech companies and research institutions, as well as anyone with foundational knowledge of machine learning will find this resource invaluable for advancing their skills in LLMOps.

Download or read book Hands On Genetic Algorithms with Python written by Eyal Wirsansky and published by Packt Publishing Ltd. This book was released on 2024-07-12 with total page 419 pages. Available in PDF, EPUB and Kindle. Book excerpt: Explore the ever-growing world of genetic algorithms to build and enhance AI applications involving search, optimization, machine learning, deep learning, NLP, and XAI using Python libraries Key Features Learn how to implement genetic algorithms using Python libraries DEAP, scikit-learn, and NumPy Take advantage of cloud computing technology to increase the performance of your solutions Discover bio-inspired algorithms such as particle swarm optimization (PSO) and NEAT Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionWritten by Eyal Wirsansky, a senior data scientist and AI researcher with over 25 years of experience and a research background in genetic algorithms and neural networks, Hands-On Genetic Algorithms with Python offers expert insights and practical knowledge to master genetic algorithms. After an introduction to genetic algorithms and their principles of operation, you’ll find out how they differ from traditional algorithms and the types of problems they can solve, followed by applying them to search and optimization tasks such as planning, scheduling, gaming, and analytics. As you progress, you’ll delve into explainable AI and apply genetic algorithms to AI to improve machine learning and deep learning models, as well as tackle reinforcement learning and NLP tasks. This updated second edition further expands on applying genetic algorithms to NLP and XAI and speeding up genetic algorithms with concurrency and cloud computing. You’ll also get to grips with the NEAT algorithm. The book concludes with an image reconstruction project and other related technologies for future applications. By the end of this book, you’ll have gained hands-on experience in applying genetic algorithms across a variety of fields, with emphasis on artificial intelligence with Python.What you will learn Use genetic algorithms to solve planning, scheduling, gaming, and analytics problems Create reinforcement learning, NLP, and explainable AI applications Enhance the performance of ML models and optimize deep learning architecture Deploy genetic algorithms using client-server architectures, enhancing scalability and computational efficiency Explore how images can be reconstructed using a set of semi-transparent shapes Delve into topics like elitism, niching, and multiplicity in genetic solutions to enhance optimization strategies and solution diversity Who this book is for If you’re a data scientist, software developer, AI enthusiast who wants to break into the world of genetic algorithms and apply them to real-world, intelligent applications as quickly as possible, this book is for you. Working knowledge of the Python programming language is required to get started with this book.

Download or read book Generative AI Foundations in Python written by Carlos Rodriguez and published by Packt Publishing Ltd. This book was released on 2024-07-26 with total page 190 pages. Available in PDF, EPUB and Kindle. Book excerpt: Begin your generative AI journey with Python as you explore large language models, understand responsible generative AI practices, and apply your knowledge to real-world applications through guided tutorials Key Features Gain expertise in prompt engineering, LLM fine-tuning, and domain adaptation Use transformers-based LLMs and diffusion models to implement AI applications Discover strategies to optimize model performance, address ethical considerations, and build trust in AI systems Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionThe intricacies and breadth of generative AI (GenAI) and large language models can sometimes eclipse their practical application. It is pivotal to understand the foundational concepts needed to implement generative AI. This guide explains the core concepts behind -of-the-art generative models by combining theory and hands-on application. Generative AI Foundations in Python begins by laying a foundational understanding, presenting the fundamentals of generative LLMs and their historical evolution, while also setting the stage for deeper exploration. You’ll also understand how to apply generative LLMs in real-world applications. The book cuts through the complexity and offers actionable guidance on deploying and fine-tuning pre-trained language models with Python. Later, you’ll delve into topics such as task-specific fine-tuning, domain adaptation, prompt engineering, quantitative evaluation, and responsible AI, focusing on how to effectively and responsibly use generative LLMs. By the end of this book, you’ll be well-versed in applying generative AI capabilities to real-world problems, confidently navigating its enormous potential ethically and responsibly.What you will learn Discover the fundamentals of GenAI and its foundations in NLP Dissect foundational generative architectures including GANs, transformers, and diffusion models Find out how to fine-tune LLMs for specific NLP tasks Understand transfer learning and fine-tuning to facilitate domain adaptation, including fields such as finance Explore prompt engineering, including in-context learning, templatization, and rationalization through chain-of-thought and RAG Implement responsible practices with generative LLMs to minimize bias, toxicity, and other harmful outputs Who this book is for This book is for developers, data scientists, and machine learning engineers embarking on projects driven by generative AI. A general understanding of machine learning and deep learning, as well as some proficiency with Python, is expected.

Download or read book Unlocking Data with Generative AI and RAG written by Keith Bourne and published by Packt Publishing Ltd. This book was released on 2024-09-27 with total page 346 pages. Available in PDF, EPUB and Kindle. Book excerpt: Leverage cutting-edge generative AI techniques such as RAG to realize the potential of your data and drive innovation as well as gain strategic advantage Key Features Optimize data retrieval and generation using vector databases Boost decision-making and automate workflows with AI agents Overcome common challenges in implementing real-world RAG systems Purchase of the print or Kindle book includes a free PDF eBook Book Description Generative AI is helping organizations tap into their data in new ways, with retrieval-augmented generation (RAG) combining the strengths of large language models (LLMs) with internal data for more intelligent and relevant AI applications. The author harnesses his decade of ML experience in this book to equip you with the strategic insights and technical expertise needed when using RAG to drive transformative outcomes. The book explores RAG’s role in enhancing organizational operations by blending theoretical foundations with practical techniques. You’ll work with detailed coding examples using tools such as LangChain and Chroma’s vector database to gain hands-on experience in integrating RAG into AI systems. The chapters contain real-world case studies and sample applications that highlight RAG’s diverse use cases, from search engines to chatbots. You’ll learn proven methods for managing vector databases, optimizing data retrieval, effective prompt engineering, and quantitatively evaluating performance. The book also takes you through advanced integrations of RAG with cutting-edge AI agents and emerging non-LLM technologies. By the end of this book, you’ll be able to successfully deploy RAG in business settings, address common challenges, and push the boundaries of what’s possible with this revolutionary AI technique. What you will learn Understand RAG principles and their significance in generative AI Integrate LLMs with internal data for enhanced operations Master vectorization, vector databases, and vector search techniques Develop skills in prompt engineering specific to RAG and design for precise AI responses Familiarize yourself with AI agents' roles in facilitating sophisticated RAG applications Overcome scalability, data quality, and integration issues Discover strategies for optimizing data retrieval and AI interpretability Who this book is for This book is for AI researchers, data scientists, software developers, and business analysts looking to leverage RAG and generative AI to enhance data retrieval, improve AI accuracy, and drive innovation. It is particularly suited for anyone with a foundational understanding of AI who seeks practical, hands-on learning. The book offers real-world coding examples and strategies for implementing RAG effectively, making it accessible to both technical and non-technical audiences. A basic understanding of Python and Jupyter Notebooks is required.

Download or read book Azure Cookbook written by Reza Salehi and published by "O'Reilly Media, Inc.". This book was released on 2022-10-10 with total page 335 pages. Available in PDF, EPUB and Kindle. Book excerpt: How do you deal with the problems you face when using Azure? This practical guide provides over 75 recipes to help you to work with common Azure issues in everyday scenarios. That includes key tasks like setting up permissions for a storage account, working with Cosmos DB APIs, managing Azure role-based access control, governing your Azure subscriptions using Azure Policy, and much more. Author Reza Salehi has assembled real-world recipes that enable you to grasp key Azure services and concepts quickly. Each recipe includes CLI scripts that you can execute in your own Azure account. Recipes also explain the approach and provide meaningful context. The solutions in this cookbook will take you beyond theory and help you understand Azure services in practice. You'll find recipes that let you: Store data in an Azure storage account or in a data lake Work with relational and nonrelational databases in Azure Manage role-based access control (RBAC) for Azure resources Safeguard secrets in Azure Key Vault Govern your Azure subscription using Azure Policy Use CLI code to construct your application or fix a particular problem

Download or read book Flask Framework Cookbook written by Shalabh Aggarwal and published by Packt Publishing Ltd. This book was released on 2023-07-28 with total page 318 pages. Available in PDF, EPUB and Kindle. Book excerpt: Design and deploy robust state-of-the-art web applications using Flask 2.x and Python 3 frameworks and libraries for streamlined development and optimal performance Purchase of the print or Kindle book includes a free PDF eBook Key Features A practical and rich companion guide for web developers, offering real-world situations and use cases to learn Flask Get the most out of the powerful Flask framework while preserving the flexibility of your design choices Write cleaner, testable, and maintainable code with the help of sample apps Book DescriptionDiscover what makes Flask, the lightweight Python web framework, popular, as you delve into its modular design that enables the development of scalable web apps. With this practical guide, you'll explore modern solutions, recommended design patterns, and best practices for Flask web development. Updated to the latest version of Flask and Python, this third edition of the Flask Framework Cookbook moves away from the outdated libraries, updates content to incorporate new coding patterns, and introduces recipes for the latest tools. You'll explore different ways to integrate with GPT to build AI-ready Flask applications. The book starts with an exploration of Flask application configurations and then guides you through working with templates and understanding the ORM and view layers. You’ll also be able to write an admin interface and get to grips with testing using the factory pattern, debugging, and logging errors. Then you’ll discover different ways of using Flask to create, deploy, and manage microservices using AWS, GCP, and Kubernetes. Finally, you’ll gain insights into various deployment and post-deployment techniques for platforms such as Apache, Tornado, and Datadog. By the end of this book, you'll have acquired the knowledge necessary to write Flask applications that cater to a wide range of use cases in the best possible way and scale them using standard industry practices.What you will learn Explore advanced templating and data modeling techniques Discover effective debugging, logging, and error-handling techniques in Flask Work with different types of databases, including RDBMS and NoSQL Integrate Flask with different technologies such as Redis, Sentry, and Datadog Deploy and package Flask applications with Docker and Kubernetes Integrate GPT with your Flask application to build future-ready platforms Implement continuous integration and continuous deployment (CI/CD) to ensure efficient and consistent updates to your Flask web applications Who this book is forIf you are a web developer seeking to expand your knowledge of developing scalable and production-ready applications in Flask, this is the book for you. It is also highly valuable if you are already aware of Flask's major extensions and want to leverage them for better application development. This book will come handy as a quick reference for specific topic on Flask, its popular extensions, or specific use cases. It assumes basic Python programming experience, as well as familiarity with web development and related terminology.

Download or read book Python Data Cleaning Cookbook written by Michael Walker and published by Packt Publishing Ltd. This book was released on 2024-05-31 with total page 487 pages. Available in PDF, EPUB and Kindle. Book excerpt: Learn the intricacies of data description, issue identification, and practical problem-solving, armed with essential techniques and expert tips. Key Features Get to grips with new techniques for data preprocessing and cleaning for machine learning and NLP models Use new and updated AI tools and techniques for data cleaning tasks Clean, monitor, and validate large data volumes to diagnose problems using cutting-edge methodologies including Machine learning and AI Book DescriptionJumping into data analysis without proper data cleaning will certainly lead to incorrect results. The Python Data Cleaning Cookbook - Second Edition will show you tools and techniques for cleaning and handling data with Python for better outcomes. Fully updated to the latest version of Python and all relevant tools, this book will teach you how to manipulate and clean data to get it into a useful form. he current edition focuses on advanced techniques like machine learning and AI-specific approaches and tools for data cleaning along with the conventional ones. The book also delves into tips and techniques to process and clean data for ML, AI, and NLP models. You will learn how to filter and summarize data to gain insights and better understand what makes sense and what does not, along with discovering how to operate on data to address the issues you've identified. Next, you’ll cover recipes for using supervised learning and Naive Bayes analysis to identify unexpected values and classification errors and generate visualizations for exploratory data analysis (EDA) to identify unexpected values. Finally, you’ll build functions and classes that you can reuse without modification when you have new data. By the end of this Data Cleaning book, you'll know how to clean data and diagnose problems within it.What you will learn Using OpenAI tools for various data cleaning tasks Producing summaries of the attributes of datasets, columns, and rows Anticipating data-cleaning issues when importing tabular data into pandas Applying validation techniques for imported tabular data Improving your productivity in pandas by using method chaining Recognizing and resolving common issues like dates and IDs Setting up indexes to streamline data issue identification Using data cleaning to prepare your data for ML and AI models Who this book is for This book is for anyone looking for ways to handle messy, duplicate, and poor data using different Python tools and techniques. The book takes a recipe-based approach to help you to learn how to clean and manage data with practical examples. Working knowledge of Python programming is all you need to get the most out of the book.

Download or read book TensorFlow 2 Reinforcement Learning Cookbook written by Praveen Palanisamy and published by Packt Publishing Ltd. This book was released on 2021-01-15 with total page 473 pages. Available in PDF, EPUB and Kindle. Book excerpt: Discover recipes for developing AI applications to solve a variety of real-world business problems using reinforcement learning Key FeaturesDevelop and deploy deep reinforcement learning-based solutions to production pipelines, products, and servicesExplore popular reinforcement learning algorithms such as Q-learning, SARSA, and the actor-critic methodCustomize and build RL-based applications for performing real-world tasksBook Description With deep reinforcement learning, you can build intelligent agents, products, and services that can go beyond computer vision or perception to perform actions. TensorFlow 2.x is the latest major release of the most popular deep learning framework used to develop and train deep neural networks (DNNs). This book contains easy-to-follow recipes for leveraging TensorFlow 2.x to develop artificial intelligence applications. Starting with an introduction to the fundamentals of deep reinforcement learning and TensorFlow 2.x, the book covers OpenAI Gym, model-based RL, model-free RL, and how to develop basic agents. You'll discover how to implement advanced deep reinforcement learning algorithms such as actor-critic, deep deterministic policy gradients, deep-Q networks, proximal policy optimization, and deep recurrent Q-networks for training your RL agents. As you advance, you’ll explore the applications of reinforcement learning by building cryptocurrency trading agents, stock/share trading agents, and intelligent agents for automating task completion. Finally, you'll find out how to deploy deep reinforcement learning agents to the cloud and build cross-platform apps using TensorFlow 2.x. By the end of this TensorFlow book, you'll have gained a solid understanding of deep reinforcement learning algorithms and their implementations from scratch. What you will learnBuild deep reinforcement learning agents from scratch using the all-new TensorFlow 2.x and Keras APIImplement state-of-the-art deep reinforcement learning algorithms using minimal codeBuild, train, and package deep RL agents for cryptocurrency and stock tradingDeploy RL agents to the cloud and edge to test them by creating desktop, web, and mobile apps and cloud servicesSpeed up agent development using distributed DNN model trainingExplore distributed deep RL architectures and discover opportunities in AIaaS (AI as a Service)Who this book is for The book is for machine learning application developers, AI and applied AI researchers, data scientists, deep learning practitioners, and students with a basic understanding of reinforcement learning concepts who want to build, train, and deploy their own reinforcement learning systems from scratch using TensorFlow 2.x.