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Book ChatGPT vs  Gemini Chat  A Comparative Study on Language Model Performance

Download or read book ChatGPT vs Gemini Chat A Comparative Study on Language Model Performance written by M.B. Chatfield and published by M.B. Chatfield. This book was released on with total page 197 pages. Available in PDF, EPUB and Kindle. Book excerpt: ChatGPT and Gemini Chat are two of the most powerful language models available. They can be used to perform a variety of tasks, including generating human-quality text, translating languages, and answering questions. Both models have their own strengths and weaknesses. ChatGPT is generally better at generating creative text formats, such as poems, code, scripts, musical pieces, email, letters, etc., while Gemini Chat is better at answering questions in an informative way, even if they are open ended, challenging, or strange. This book provides a comprehensive overview of ChatGPT and Gemini Chat, including their strengths and weaknesses, how they work, and how to use them. It is a valuable resource for anyone who wants to learn more about these powerful language models.

Book ChatGPT and Gemini Chat 101  A Beginner s Guide to Language Models

Download or read book ChatGPT and Gemini Chat 101 A Beginner s Guide to Language Models written by M.B. Chatfield and published by M.B. Chatfield. This book was released on with total page 163 pages. Available in PDF, EPUB and Kindle. Book excerpt: Embark on a journey to explore the fascinating world of language models, with ChatGPT and Gemini Chat as your guides. In this beginner-friendly guide, you will discover the basics of language models, including their history, development, and applications. You will also learn how to use ChatGPT and Gemini Chat, two powerful language models created by OpenAI and Google AI, respectively. Throughout the guide, you will: Gain a comprehensive understanding of language models and their role in artificial intelligence (AI). Explore the capabilities of ChatGPT and Gemini Chat, including their ability to generate human-quality text, translate languages, write different kinds of creative content, and answer your questions in an informative way. This book is perfect for anyone who wants to learn the basics of language models and how to use them. So what are you waiting for? Start your adventure into the world of language models today! With ChatGPT and Gemini Chat as your guides, you're sure to have an enriching and enlightening experience. Join us as we explore the endless possibilities of language models and their impact on the future.

Book Python 3 and Machine Learning Using ChatGPT   GPT 4

Download or read book Python 3 and Machine Learning Using ChatGPT GPT 4 written by Oswald Campesato and published by Stylus Publishing, LLC. This book was released on 2024-05-22 with total page 304 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is designed to bridge the gap between theoretical knowledge and practical application in the fields of Python programming, machine learning, and the innovative use of ChatGPT-4 in data science. The book is structured to facilitate a deep understanding of several core topics. It begins with a detailed introduction to Pandas, a cornerstone Python library for data manipulation and analysis. Next, it explores a variety of machine learning classifiers from kNN to SVMs. In later chapters, it discusses the capabilities of GPT-4, and how its application enhances traditional linear regression analysis. Finally, the book covers the innovative use of ChatGPT in data visualization. This segment focuses on how AI can transform data into compelling visual stories, making complex results accessible and understandable. It includes material on AI apps, GANs, and DALL-E. Companion files are available for downloading with code and figures from the text. FEATURES: Includes practical tutorials designed to provide hands-on experience, reinforcing learning through practice Provides coverage of the latest Python tools using state-of-the-art libraries essential for modern data scientists Companion files with source code, datasets, and figures are available for downloading

Book Annals of the Former World

    Book Details:
  • Author : John McPhee
  • Publisher : Farrar, Straus and Giroux
  • Release : 2000-06-15
  • ISBN : 0374708460
  • Pages : 448 pages

Download or read book Annals of the Former World written by John McPhee and published by Farrar, Straus and Giroux. This book was released on 2000-06-15 with total page 448 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Pulitzer Prize-winning view of the continent, across the fortieth parallel and down through 4.6 billion years Twenty years ago, when John McPhee began his journeys back and forth across the United States, he planned to describe a cross section of North America at about the fortieth parallel and, in the process, come to an understanding not only of the science but of the style of the geologists he traveled with. The structure of the book never changed, but its breadth caused him to complete it in stages, under the overall title Annals of the Former World. Like the terrain it covers, Annals of the Former World tells a multilayered tale, and the reader may choose one of many paths through it. As clearly and succinctly written as it is profoundly informed, this is our finest popular survey of geology and a masterpiece of modern nonfiction. Annals of the Former World is the winner of the 1999 Pulitzer Prize for Nonfiction.

Book Opinion Mining and Sentiment Analysis

Download or read book Opinion Mining and Sentiment Analysis written by Bo Pang and published by Now Publishers Inc. This book was released on 2008 with total page 149 pages. Available in PDF, EPUB and Kindle. Book excerpt: This survey covers techniques and approaches that promise to directly enable opinion-oriented information-seeking systems.

Book Best

    Book Details:
  • Author : Alan D. Thompson
  • Publisher : Createspace Independent Publishing Platform
  • Release : 2013-10-20
  • ISBN : 9781493541393
  • Pages : 200 pages

Download or read book Best written by Alan D. Thompson and published by Createspace Independent Publishing Platform. This book was released on 2013-10-20 with total page 200 pages. Available in PDF, EPUB and Kindle. Book excerpt: Being good at something is simple. Being great is easier now than ever before. But how do you go about being your absolute best? You are now holding in your hands an instruction manual, a help file, a list of shortcuts for living your best life. Offering personal stories from the author's own life, distilled wisdom from prominent teachers, and practical action to help you connect all the dots. It opens new ways of thinking about who you are, and how much more you can become. Best's bite-size chapters are filled with clear explanations and the occasional question, one of which is: “What would it take to stop driving in traffic, and to start flying in your own jet stream?” To find out: sit down, fasten your seatbelt, start reading, and prepare for lift-off.

Book Transfer Learning for Natural Language Processing

Download or read book Transfer Learning for Natural Language Processing written by Paul Azunre and published by Simon and Schuster. This book was released on 2021-08-31 with total page 262 pages. Available in PDF, EPUB and Kindle. Book excerpt: Build custom NLP models in record time by adapting pre-trained machine learning models to solve specialized problems. Summary In Transfer Learning for Natural Language Processing you will learn: Fine tuning pretrained models with new domain data Picking the right model to reduce resource usage Transfer learning for neural network architectures Generating text with generative pretrained transformers Cross-lingual transfer learning with BERT Foundations for exploring NLP academic literature Training deep learning NLP models from scratch is costly, time-consuming, and requires massive amounts of data. In Transfer Learning for Natural Language Processing, DARPA researcher Paul Azunre reveals cutting-edge transfer learning techniques that apply customizable pretrained models to your own NLP architectures. You’ll learn how to use transfer learning to deliver state-of-the-art results for language comprehension, even when working with limited label data. Best of all, you’ll save on training time and computational costs. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the technology Build custom NLP models in record time, even with limited datasets! Transfer learning is a machine learning technique for adapting pretrained machine learning models to solve specialized problems. This powerful approach has revolutionized natural language processing, driving improvements in machine translation, business analytics, and natural language generation. About the book Transfer Learning for Natural Language Processing teaches you to create powerful NLP solutions quickly by building on existing pretrained models. This instantly useful book provides crystal-clear explanations of the concepts you need to grok transfer learning along with hands-on examples so you can practice your new skills immediately. As you go, you’ll apply state-of-the-art transfer learning methods to create a spam email classifier, a fact checker, and more real-world applications. What's inside Fine tuning pretrained models with new domain data Picking the right model to reduce resource use Transfer learning for neural network architectures Generating text with pretrained transformers About the reader For machine learning engineers and data scientists with some experience in NLP. About the author Paul Azunre holds a PhD in Computer Science from MIT and has served as a Principal Investigator on several DARPA research programs. Table of Contents PART 1 INTRODUCTION AND OVERVIEW 1 What is transfer learning? 2 Getting started with baselines: Data preprocessing 3 Getting started with baselines: Benchmarking and optimization PART 2 SHALLOW TRANSFER LEARNING AND DEEP TRANSFER LEARNING WITH RECURRENT NEURAL NETWORKS (RNNS) 4 Shallow transfer learning for NLP 5 Preprocessing data for recurrent neural network deep transfer learning experiments 6 Deep transfer learning for NLP with recurrent neural networks PART 3 DEEP TRANSFER LEARNING WITH TRANSFORMERS AND ADAPTATION STRATEGIES 7 Deep transfer learning for NLP with the transformer and GPT 8 Deep transfer learning for NLP with BERT and multilingual BERT 9 ULMFiT and knowledge distillation adaptation strategies 10 ALBERT, adapters, and multitask adaptation strategies 11 Conclusions

Book The Language of Coaching

Download or read book The Language of Coaching written by Nick Winkelman and published by Human Kinetics. This book was released on 2020-04-21 with total page 337 pages. Available in PDF, EPUB and Kindle. Book excerpt: Try to recall the best coach you’ve ever had. Consider what differentiated them from other coaches; what made them so effective? Was it their knowledge and programming, or did it come down to the way they communicated with you and the way they made you feel? While the former are critical, it is a coach’s words that set them apart from the rest. The Language of Coaching focuses on the impact that communication has on an individual’s ability to learn and perform a movement. Written by performance coach Nick Winkelman, the book examines how instruction, feedback, and cueing can significantly affect training outcomes. Grounded in motor learning and the science of attentional focus, Winkelman takes you on a journey, guiding you through practical coaching frameworks that will help you adapt your language to the learning needs of those you support. Packed with stunning visuals, the book provides over 25 movement sequences that outline different types of coaching cues, including a visual depiction of unique analogies, such as a sprinter taking off like a jet or an athlete loading into a jump like a spring. The book is filled with a comprehensive collection of cueing frameworks that guide you through the process of creating your own cues for any movement you want to teach. You will also learn how to engage in more productive conversation with your athletes through sample dialogue that uses the book’s cueing philosophy. Whether you are new to coaching or a seasoned veteran, The Language of Coaching will help you grow as a communicator and learn how to coach the person with the same precision as you do the program. Earn continuing education credits/units! A continuing education exam that uses this book is also available. It may be purchased separately or as part of a package that includes both the book and exam.

Book The Open Revolution

    Book Details:
  • Author : Rufus Pollock
  • Publisher :
  • Release : 2018-05-30
  • ISBN : 9781983033223
  • Pages : 126 pages

Download or read book The Open Revolution written by Rufus Pollock and published by . This book was released on 2018-05-30 with total page 126 pages. Available in PDF, EPUB and Kindle. Book excerpt: Forget everything you think you know about the digital age. It's not about privacy, surveillance, AI or blockchain-it's about ownership. Because, in a digital age, who owns information controls the future.

Book Language and the Internet

    Book Details:
  • Author : David Crystal
  • Publisher : Cambridge University Press
  • Release : 2006-08-31
  • ISBN : 0521868599
  • Pages : 276 pages

Download or read book Language and the Internet written by David Crystal and published by Cambridge University Press. This book was released on 2006-08-31 with total page 276 pages. Available in PDF, EPUB and Kindle. Book excerpt: Publisher description

Book Deep Learning with Structured Data

Download or read book Deep Learning with Structured Data written by Mark Ryan and published by Simon and Schuster. This book was released on 2020-12-08 with total page 262 pages. Available in PDF, EPUB and Kindle. Book excerpt: Deep Learning with Structured Data teaches you powerful data analysis techniques for tabular data and relational databases. Summary Deep learning offers the potential to identify complex patterns and relationships hidden in data of all sorts. Deep Learning with Structured Data shows you how to apply powerful deep learning analysis techniques to the kind of structured, tabular data you'll find in the relational databases that real-world businesses depend on. Filled with practical, relevant applications, this book teaches you how deep learning can augment your existing machine learning and business intelligence systems. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the technology Here’s a dirty secret: Half of the time in most data science projects is spent cleaning and preparing data. But there’s a better way: Deep learning techniques optimized for tabular data and relational databases deliver insights and analysis without requiring intense feature engineering. Learn the skills to unlock deep learning performance with much less data filtering, validating, and scrubbing. About the book Deep Learning with Structured Data teaches you powerful data analysis techniques for tabular data and relational databases. Get started using a dataset based on the Toronto transit system. As you work through the book, you’ll learn how easy it is to set up tabular data for deep learning, while solving crucial production concerns like deployment and performance monitoring. What's inside When and where to use deep learning The architecture of a Keras deep learning model Training, deploying, and maintaining models Measuring performance About the reader For readers with intermediate Python and machine learning skills. About the author Mark Ryan is a Data Science Manager at Intact Insurance. He holds a Master's degree in Computer Science from the University of Toronto. Table of Contents 1 Why deep learning with structured data? 2 Introduction to the example problem and Pandas dataframes 3 Preparing the data, part 1: Exploring and cleansing the data 4 Preparing the data, part 2: Transforming the data 5 Preparing and building the model 6 Training the model and running experiments 7 More experiments with the trained model 8 Deploying the model 9 Recommended next steps

Book The Measure of All Minds

    Book Details:
  • Author : José Hernández-Orallo
  • Publisher : Cambridge University Press
  • Release : 2017-01-11
  • ISBN : 1316943208
  • Pages : 739 pages

Download or read book The Measure of All Minds written by José Hernández-Orallo and published by Cambridge University Press. This book was released on 2017-01-11 with total page 739 pages. Available in PDF, EPUB and Kindle. Book excerpt: Are psychometric tests valid for a new reality of artificial intelligence systems, technology-enhanced humans, and hybrids yet to come? Are the Turing Test, the ubiquitous CAPTCHAs, and the various animal cognition tests the best alternatives? In this fascinating and provocative book, José Hernández-Orallo formulates major scientific questions, integrates the most significant research developments, and offers a vision of the universal evaluation of cognition. By replacing the dominant anthropocentric stance with a universal perspective where living organisms are considered as a special case, long-standing questions in the evaluation of behavior can be addressed in a wider landscape. Can we derive task difficulty intrinsically? Is a universal g factor - a common general component for all abilities - theoretically possible? Using algorithmic information theory as a foundation, the book elaborates on the evaluation of perceptual, developmental, social, verbal and collective features and critically analyzes what the future of intelligence might look like.

Book Qualitative Data Analysis

Download or read book Qualitative Data Analysis written by Ian Dey and published by Routledge. This book was released on 2003-09-02 with total page 309 pages. Available in PDF, EPUB and Kindle. Book excerpt: Qualitative Data Analysis shows that learning how to analyse qualitative data by computer can be fun. Written in a stimulating style, with examples drawn mainly from every day life and contemporary humour, it should appeal to a wide audience.

Book Artificial Intelligence in Healthcare

Download or read book Artificial Intelligence in Healthcare written by Adam Bohr and published by Academic Press. This book was released on 2020-06-21 with total page 385 pages. Available in PDF, EPUB and Kindle. Book excerpt: Artificial Intelligence (AI) in Healthcare is more than a comprehensive introduction to artificial intelligence as a tool in the generation and analysis of healthcare data. The book is split into two sections where the first section describes the current healthcare challenges and the rise of AI in this arena. The ten following chapters are written by specialists in each area, covering the whole healthcare ecosystem. First, the AI applications in drug design and drug development are presented followed by its applications in the field of cancer diagnostics, treatment and medical imaging. Subsequently, the application of AI in medical devices and surgery are covered as well as remote patient monitoring. Finally, the book dives into the topics of security, privacy, information sharing, health insurances and legal aspects of AI in healthcare. Highlights different data techniques in healthcare data analysis, including machine learning and data mining Illustrates different applications and challenges across the design, implementation and management of intelligent systems and healthcare data networks Includes applications and case studies across all areas of AI in healthcare data

Book Artificial Intelligence in Education

Download or read book Artificial Intelligence in Education written by Wayne Holmes and published by . This book was released on 2019-02-28 with total page 244 pages. Available in PDF, EPUB and Kindle. Book excerpt: "The landscape for education has been rapidly changing in the last years: demographic changes affecting the makeup of families, multiple school options available to children, wealth disparities, the global economy demanding new skills from workers, and continued breakthroughs in technology are some of the factors impacting education. Given these changes, how can schools continue to prepare students for the future? In a world where information is readily available online, how can schools continue to be relevant? The emergence of Artificial Intelligence (AI) has exacerbated the need to have these conversations. Its impact on education and the multiple possibilities that it offers are putting pressure on educational leaders to reformulate the school curriculum and the channels to deliver it. The book "Artificial Intelligence in Education, Promises and Implications for Teaching and Learning" by the Center for Curriculum Redesign immerses the reader in a discussion on what to teach students in the era of AI and examines how AI is already demanding much needed updates to the school curriculum, including modernizing its content, focusing on core concepts, and embedding interdisciplinary themes and competencies with the end goal of making learning more enjoyable and useful in students' lives. The second part of the book dives into the history of AI in education, its techniques and applications -including the way AI can help teachers be more effective, and finishes on a reflection about the social aspects of AI. This book is a must-read for educators and policy-makers who want to prepare schools to face the uncertainties of the future and keep them relevant." --Amada Torres, VP, Studies, Insights, and Research, National Association of Independent School (NAIS) "The rapid advances in technology in recent decades have already brought about substantial changes in education, opening up new opportunities to teach and learn anywhere anytime and providing new tools and methods to improve learning outcomes and support innovative teaching and learning.Research into artificial intelligence and machine learning in education goes back to the late 1970s. Artificial intelligence methods were generally employed in two ways: to design and facilitate interactive learning environments that would support learning by doing, and to design and implement tutoring systems by adapting instructions with respect to the students' knowledge state.But this is just the beginning. As Artificial Intelligence in Education shows, AI is increasingly used in education and learning contexts. The collision of three areas - data, computation and education - is set to have far-reaching consequences, raising fundamental questions about the nature of education: what is taught and how it is taught. Artificial Intelligence in Education is an important, if at times disturbing, contribution to the debate on AI and provides a detailed analysis on how it may affect the way teachers and students engage in education. The book describes how artificial intelligence may impact on curriculum design, on the individualisation of learning, and on assessment, offering some tantalising glimpses into the future (the end of exams, your very own lifelong learning companion) while not falling victim to tech-hype. The enormous ethical, technical and pedagogical challenges ahead are spelt out, and there is a real risk that the rapid advances in artificial intelligence products and services will outstrip education systems' capacity to understand, manage and integrate them appropriately. As the book concludes: "We can either leave it to others (the computer scientists, AI engineers and big tech companies) to decide how artificial intelligence in education unfolds, or we can engage in productive dialogue."I commend this book to anyone concerned with the future of education in a digital world." --Marc Durando, Executive Director, European Schoolnet

Book Machine Learning with PyTorch and Scikit Learn

Download or read book Machine Learning with PyTorch and Scikit Learn written by Sebastian Raschka and published by Packt Publishing Ltd. This book was released on 2022-02-25 with total page 775 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book of the bestselling and widely acclaimed Python Machine Learning series is a comprehensive guide to machine and deep learning using PyTorch s simple to code framework. Purchase of the print or Kindle book includes a free eBook in PDF format. Key Features Learn applied machine learning with a solid foundation in theory Clear, intuitive explanations take you deep into the theory and practice of Python machine learning Fully updated and expanded to cover PyTorch, transformers, XGBoost, graph neural networks, and best practices Book DescriptionMachine Learning with PyTorch and Scikit-Learn is a comprehensive guide to machine learning and deep learning with PyTorch. It acts as both a step-by-step tutorial and a reference you'll keep coming back to as you build your machine learning systems. Packed with clear explanations, visualizations, and examples, the book covers all the essential machine learning techniques in depth. While some books teach you only to follow instructions, with this machine learning book, we teach the principles allowing you to build models and applications for yourself. Why PyTorch? PyTorch is the Pythonic way to learn machine learning, making it easier to learn and simpler to code with. This book explains the essential parts of PyTorch and how to create models using popular libraries, such as PyTorch Lightning and PyTorch Geometric. You will also learn about generative adversarial networks (GANs) for generating new data and training intelligent agents with reinforcement learning. Finally, this new edition is expanded to cover the latest trends in deep learning, including graph neural networks and large-scale transformers used for natural language processing (NLP). This PyTorch book is your companion to machine learning with Python, whether you're a Python developer new to machine learning or want to deepen your knowledge of the latest developments.What you will learn Explore frameworks, models, and techniques for machines to learn from data Use scikit-learn for machine learning and PyTorch for deep learning Train machine learning classifiers on images, text, and more Build and train neural networks, transformers, and boosting algorithms Discover best practices for evaluating and tuning models Predict continuous target outcomes using regression analysis Dig deeper into textual and social media data using sentiment analysis Who this book is for If you have a good grasp of Python basics and want to start learning about machine learning and deep learning, then this is the book for you. This is an essential resource written for developers and data scientists who want to create practical machine learning and deep learning applications using scikit-learn and PyTorch. Before you get started with this book, you’ll need a good understanding of calculus, as well as linear algebra.

Book Real World Natural Language Processing

Download or read book Real World Natural Language Processing written by Masato Hagiwara and published by Simon and Schuster. This book was released on 2021-12-14 with total page 334 pages. Available in PDF, EPUB and Kindle. Book excerpt: Voice assistants, automated customer service agents, and other cutting-edge human-to-computer interactions rely on accurately interpreting language as it is written and spoken. Real-world Natural Language Processing teaches you how to create practical NLP applications without getting bogged down in complex language theory and the mathematics of deep learning. In this engaging book, you''ll explore the core tools and techniques required to build a huge range of powerful NLP apps. about the technology Natural language processing is the part of AI dedicated to understanding and generating human text and speech. NLP covers a wide range of algorithms and tasks, from classic functions such as spell checkers, machine translation, and search engines to emerging innovations like chatbots, voice assistants, and automatic text summarization. Wherever there is text, NLP can be useful for extracting meaning and bridging the gap between humans and machines. about the book Real-world Natural Language Processing teaches you how to create practical NLP applications using Python and open source NLP libraries such as AllenNLP and Fairseq. In this practical guide, you''ll begin by creating a complete sentiment analyzer, then dive deep into each component to unlock the building blocks you''ll use in all different kinds of NLP programs. By the time you''re done, you''ll have the skills to create named entity taggers, machine translation systems, spelling correctors, and language generation systems. what''s inside Design, develop, and deploy basic NLP applications NLP libraries such as AllenNLP and Fairseq Advanced NLP concepts such as attention and transfer learning about the reader Aimed at intermediate Python programmers. No mathematical or machine learning knowledge required. about the author Masato Hagiwara received his computer science PhD from Nagoya University in 2009, focusing on Natural Language Processing and machine learning. He has interned at Google and Microsoft Research, and worked at Baidu Japan, Duolingo, and Rakuten Institute of Technology. He now runs his own consultancy business advising clients, including startups and research institutions.