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Author: Henry Habib
Publisher: Packt Publishing Ltd
ISBN: 1805125737
Category : Computers
Languages : en
Pages : 192
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Book Description
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.
Author: Henry Habib
Publisher: Packt Publishing Ltd
ISBN: 1805125737
Category : Computers
Languages : en
Pages : 192
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Book Description
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.
Author: Clint Bodungen
Publisher: Packt Publishing Ltd
ISBN: 1805125117
Category : Computers
Languages : en
Pages : 372
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Book Description
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.
Author: Zhenya Antić
Publisher: Packt Publishing Ltd
ISBN: 1803241446
Category : Computers
Languages : en
Pages : 312
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Book Description
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.
Author: Shalabh Aggarwal
Publisher: Packt Publishing Ltd
ISBN: 1804610003
Category : Computers
Languages : en
Pages : 318
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Book Description
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.
Author: Lior Gazit
Publisher: Packt Publishing Ltd
ISBN: 1804616389
Category : Computers
Languages : en
Pages : 340
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Book Description
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.
Author: Margarida Barreto
Publisher: Packt Publishing Ltd
ISBN: 1835089186
Category : Computers
Languages : en
Pages : 326
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Book Description
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.
Author: Lucas A. Meyer
Publisher: Packt Publishing Ltd
ISBN: 1835469590
Category : Computers
Languages : en
Pages : 252
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Book Description
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.
Author: Vincent Vandenbussche
Publisher: Packt Publishing Ltd
ISBN: 1837639728
Category : Mathematics
Languages : en
Pages : 424
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Book Description
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.
Author: Josué R. Batista
Publisher: Packt Publishing Ltd
ISBN: 1835087493
Category : Computers
Languages : en
Pages : 372
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Book Description
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.
Author: RYAN. DOAN
Publisher: Packt Publishing Ltd
ISBN: 1835887511
Category : Computers
Languages : en
Pages : 190
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Book Description
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.
