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Author: Pere Martra
Publisher: Springer Nature
ISBN:
Category :
Languages : en
Pages : 366
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Book Description
Author: Pere Martra
Publisher: Springer Nature
ISBN:
Category :
Languages : en
Pages : 366
Get Book Here
Book Description
Author: Pere Martra Manonelles
Publisher: Apress
ISBN:
Category : Computers
Languages : en
Pages : 0
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Book Description
This book offers you a hands-on experience using models from OpenAI and the Hugging Face library. You will use various tools and work on small projects, gradually applying the new knowledge you gain. The book is divided into three parts. Part one covers techniques and libraries. Here, you'll explore different techniques through small examples, preparing to build projects in the next section. You'll learn to use common libraries in the world of Large Language Models. Topics and technologies covered include chatbots, code generation, OpenAI API, Hugging Face, vector databases, LangChain, fine tuning, PEFT fine tuning, soft prompt tuning, LoRA, QLoRA, evaluating models, and Direct Preference Optimization. Part two focuses on projects. You'll create projects, understanding design decisions. Each project may have more than one possible implementation, as there is often not just one good solution. You'll also explore LLMOps-related topics. Part three delves into enterprise solutions. Large Language Models are not a standalone solution; in large corporate environments, they are one piece of the puzzle. You'll explore how to structure solutions capable of transforming organizations with thousands of employees, highlighting the main role that Large Language Models play in these new solutions. This book equips you to confidently navigate and implement Large Language Models, empowering you to tackle diverse challenges in the evolving landscape of language processing. What You Will Learn Gain practical experience by working with models from OpenAI and the Hugging Face library Use essential libraries relevant to Large Language Models, covering topics such as Chatbots, Code Generation, OpenAI API, Hugging Face, and Vector databases Create and implement projects using LLM while understanding the design decisions involved Understand the role of Large Language Models in larger corporate settings Who This Book Is For Data analysts, data science, Python developers, and software professionals interested in learning the foundations of NLP, LLMs, and the processes of building modern LLM applications for various tasks
Author: Sumit Gulwani
Publisher:
ISBN: 9781680832921
Category : Computers
Languages : en
Pages : 138
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Book Description
Program synthesis is the task of automatically finding a program in the underlying programming language that satisfies the user intent expressed in the form of some specification. Since the inception of artificial intelligence in the 1950s, this problem has been considered the holy grail of Computer Science. Despite inherent challenges in the problem such as ambiguity of user intent and a typically enormous search space of programs, the field of program synthesis has developed many different techniques that enable program synthesis in different real-life application domains. It is now used successfully in software engineering, biological discovery, compute-raided education, end-user programming, and data cleaning. In the last decade, several applications of synthesis in the field of programming by examples have been deployed in mass-market industrial products. This monograph is a general overview of the state-of-the-art approaches to program synthesis, its applications, and subfields. It discusses the general principles common to all modern synthesis approaches such as syntactic bias, oracle-guided inductive search, and optimization techniques. We then present a literature review covering the four most common state-of-the-art techniques in program synthesis: enumerative search, constraint solving, stochastic search, and deduction-based programming by examples. It concludes with a brief list of future horizons for the field.
Author: Kristian Bainey
Publisher: John Wiley & Sons
ISBN: 1394232225
Category : Business & Economics
Languages : en
Pages : 449
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Book Description
Accelerate your next project with artificial intelligence and ChatGPT In AI-Driven Project Management: Harnessing the Power of Artificial Intelligence and ChatGPT to Achieve Peak Productivity and Success, veteran IT and project management advisor Kristian Bainey delivers an insightful collection of strategies for automating the administration and management of projects. In the book, the author focuses on four key areas where project leaders can achieve improved results with AI's data-centric capabilities: minimizing surprises, minimizing bias, increasing standards, and accelerating decision making. You'll also find: Primers on the role of AI and ChatGPT in Agile, Hybrid, and Predictive approaches to project management How to accurately forecast a project with ChatGPT Techniques for crafting impactful AI strategy using AI project management principles Perfect for managers, executives, and business leaders everywhere, AI-Driven Project Management is also a must-read for project management professionals, tech professionals and enthusiasts, and anyone else interested in the intersection of artificial intelligence, machine learning, and project management.
Author: Dongdong Chen
Publisher: Taylor & Francis
ISBN: 1040096638
Category : Foreign Language Study
Languages : en
Pages : 197
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Book Description
A Hybrid Approach to Teaching Chinese through Digital Humanities, CALL, and Project-Based Learning presents an exposition of current thinking, research, and best practices in Computer-Assisted Language Learning (CALL), Digital Humanities (DH), and Project-Based Language Learning (PBLL) in the context of teaching Chinese as a foreign language (TCFL). It proposes integrating CALL and DH into PBLL to form a Digital Humanities–Augmented Technology-Enhanced Project-Based Language Learning (DATEPBLL) approach to transform student learning. By combining DH pedagogy and CALL technology with PBLL, the approach takes advantage of their synergies, which enables instructors to help students develop linguistic and cultural competency as well as 21st century skills. Case studies and best practices from experienced Chinese language teachers are presented to demonstrate the value of the DATEPBLL approach. This is the first volume that covers all three fields and makes a strong case for the importance of incorporating CALL, DH, and PBLL for effective language learning. Written for professionals in language education, including educators, curriculum designers and developers, graduate students, publishers, government personnel, and researchers, the book provides theoretical insights and practical applications of CALL, DH, and PBLL.
Author: Ivo Pinto
Publisher: Packt Publishing Ltd
ISBN: 1835889298
Category : Computers
Languages : en
Pages : 266
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Book Description
Gain a deeper understanding of AWS services by building eight real-world projects Key Features Gain practical skills in architecting, deploying, and managing applications on AWS from seasoned experts Get hands-on experience by building different architectures in an easy-to-follow manner Understand the purpose of different aspects in AWS, and how to make the most of them Purchase of the print or Kindle book includes a free PDF eBook Book Description Tired of resumes that get lost in the pile? This book is your roadmap to creating an in-demand AWS portfolio that grabs attention and gets you hired.This comprehensive guide unlocks the vast potential of AWS for developers of all levels. Inside, you'll find invaluable guidance for crafting stunning websites with S3, CloudFront, and Route53. You'll build robust and scalable applications, such as recipe-sharing platforms, using DynamoDB and Elastic Load Balancing. For streamlined efficiency, the book will teach you how to develop serverless architectures with AWS Lambda and Cognito. Gradually, you'll infuse your projects with artificial intelligence by creating a photo analyzer powered by Amazon Rekognition. You'll also automate complex workflows for seamless content translation using Translate, CodePipeline, and CodeBuild. Later, you'll construct intelligent virtual assistants with Amazon Lex and Bedrock to answer web development queries. The book will also show you how to visualize your data with insightful dashboards built using Athena, Glue, and QuickSight.By the end of this book, you'll be ready to take your projects to the next level and succeed in the dynamic world of cloud computing. What you will learn Develop a professional CV website and gain familiarity with the core aspects of AWS Build a recipe-sharing application using AWS's serverless toolkit Leverage AWS AI services to create a photo friendliness analyzer for professional profiles Implement a CI/CD pipeline to automate content translation across languages Develop a web development Q&A chatbot powered by cutting-edge LLMs Build a business intelligence application to analyze website clickstream data and understand user behavior with AWS Who this book is for If you're a student who wants to start your career in cloud computing or a professional with experience in other technical areas like software development who wants to embrace a new professional path or complement your technical skills in cloud computing, this book is for you. A background in computer science or engineering and basic programming skills is recommended. All the projects in the book have theoretical explanations of the services used and do not assume any previous AWS knowledge.
Author: Yaron Haviv
Publisher: "O'Reilly Media, Inc."
ISBN: 1098136551
Category : Computers
Languages : en
Pages : 380
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Book Description
With demand for scaling, real-time access, and other capabilities, businesses need to consider building operational machine learning pipelines. This practical guide helps your company bring data science to life for different real-world MLOps scenarios. Senior data scientists, MLOps engineers, and machine learning engineers will learn how to tackle challenges that prevent many businesses from moving ML models to production. Authors Yaron Haviv and Noah Gift take a production-first approach. Rather than beginning with the ML model, you'll learn how to design a continuous operational pipeline, while making sure that various components and practices can map into it. By automating as many components as possible, and making the process fast and repeatable, your pipeline can scale to match your organization's needs. You'll learn how to provide rapid business value while answering dynamic MLOps requirements. This book will help you: Learn the MLOps process, including its technological and business value Build and structure effective MLOps pipelines Efficiently scale MLOps across your organization Explore common MLOps use cases Build MLOps pipelines for hybrid deployments, real-time predictions, and composite AI Learn how to prepare for and adapt to the future of MLOps Effectively use pre-trained models like HuggingFace and OpenAI to complement your MLOps strategy
Author: Norbert A. Streitz
Publisher: Springer Nature
ISBN: 3031599888
Category :
Languages : en
Pages : 387
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Book Description
Author: Simon Thompson
Publisher: Simon and Schuster
ISBN: 163343902X
Category : Computers
Languages : en
Pages : 270
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Book Description
Guide machine learning projects from design to production with the techniques in this unique project management guide. No ML skills required! In Managing Machine Learning Projects you’ll learn essential machine learning project management techniques, including: Understanding an ML project’s requirements Setting up the infrastructure for the project and resourcing a team Working with clients and other stakeholders Dealing with data resources and bringing them into the project for use Handling the lifecycle of models in the project Managing the application of ML algorithms Evaluating the performance of algorithms and models Making decisions about which models to adopt for delivery Taking models through development and testing Integrating models with production systems to create effective applications Steps and behaviors for managing the ethical implications of ML technology Managing Machine Learning Projects is an end-to-end guide for delivering machine learning applications on time and under budget. It lays out tools, approaches, and processes designed to handle the unique challenges of machine learning project management. You’ll follow an in-depth case study through a series of sprints and see how to put each technique into practice. The book’s strong consideration to data privacy, and community impact ensure your projects are ethical, compliant with global legislation, and avoid being exposed to failure from bias and other issues. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the Technology Ferrying machine learning projects to production often feels like navigating uncharted waters. From accounting for large data resources to tracking and evaluating multiple models, machine learning technology has radically different requirements than traditional software. Never fear! This book lays out the unique practices you’ll need to ensure your projects succeed. About the Book Managing Machine Learning Projects is an amazing source of battle-tested techniques for effective delivery of real-life machine learning solutions. The book is laid out across a series of sprints that take you from a project proposal all the way to deployment into production. You’ll learn how to plan essential infrastructure, coordinate experimentation, protect sensitive data, and reliably measure model performance. Many ML projects fail to create real value—read this book to make sure your project is a success. What's Inside Set up infrastructure and resource a team Bring data resources into a project Accurately estimate time and effort Evaluate which models to adopt for delivery Integrate models into effective applications About the Reader For anyone interested in better management of machine learning projects. No technical skills required. About the Author Simon Thompson has spent 25 years developing AI systems to create applications for use in telecoms, customer service, manufacturing and capital markets. He led the AI research program at BT Labs in the UK, and is now the Head of Data Science at GFT Technologies. Table of Contents 1 Introduction: Delivering machine learning projects is hard; let’s do it better 2 Pre-project: From opportunity to requirements 3 Pre-project: From requirements to proposal 4 Getting started 5 Diving into the problem 6 EDA, ethics, and baseline evaluations 7 Making useful models with ML 8 Testing and selection 9 Sprint 3: system building and production 10 Post project (sprint O)
Author: Marc Jansen
Publisher: BoD – Books on Demand
ISBN: 375975953X
Category :
Languages : en
Pages : 142
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Book Description
