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Chatgpt Vs Gemini Chat A Comparative Study On Language Model Performance
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Book Synopsis ChatGPT vs. Gemini Chat: A Comparative Study on Language Model Performance by : M.B. Chatfield
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 Synopsis ChatGPT Vs Google Bard AI by : A a Kabir
Download or read book ChatGPT Vs Google Bard AI written by A a Kabir and published by Independently Published. This book was released on 2023-02-10 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: "Discover the fascinating world of AI language models with "ChatGPT vs Google Bard AI: A Comparative Study of AI Language Models". Learn about the latest advancements in the field, including the revolutionary OpenAI ChatGPT and Google's innovative Bard AI. Explore the unique features, capabilities, and limitations of each model and understand their impact on the future of technology and society. Get ready to dive deep into the exciting world of AI and the impact it will have on our daily lives."
Book Synopsis ChatGPT and Gemini Chat 101: A Beginner's Guide to Language Models by : M.B. Chatfield
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 Synopsis A Comparative Study of ChatGPT and Seq2Seq Chatbot for Effective Students Advising by :
Download or read book A Comparative Study of ChatGPT and Seq2Seq Chatbot for Effective Students Advising written by and published by STAR SCHOLARS PRESS. This book was released on with total page 11 pages. Available in PDF, EPUB and Kindle. Book excerpt: A Comparative Study of ChatGPT and Seq2Seq Chatbot for Effective Students Advising
Book Synopsis Advances in Production Management Systems. Production Management Systems for Volatile, Uncertain, Complex, and Ambiguous Environments by : Matthias Thürer
Download or read book Advances in Production Management Systems. Production Management Systems for Volatile, Uncertain, Complex, and Ambiguous Environments written by Matthias Thürer and published by Springer Nature. This book was released on with total page 488 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Python 3 and Machine Learning Using ChatGPT / GPT-4 by : Oswald Campesato
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 Synopsis Explainable Artificial Intelligence by : Luca Longo
Download or read book Explainable Artificial Intelligence written by Luca Longo and published by Springer Nature. This book was released on with total page 480 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis AI-Powered Productivity by : Dr. Asma Asfour
Download or read book AI-Powered Productivity written by Dr. Asma Asfour and published by Asma Asfour. This book was released on 2024-07-29 with total page 195 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book, "AI-Powered Productivity," aims to provide a guide to understanding, utilizing AI and generative tools in various professional settings. The primary purpose of this book is to offer readers a deep dive into the concepts, tools, and practices that define the current AI landscape. From foundational principles to advanced applications, this book is structured to cater to both beginners and professionals looking to enhance their knowledge and skills in AI. This book is divided into nine chapters, each focusing on a specific aspect of AI and its practical applications: Chapter 1 introduces the basic concepts of AI, its impact on various sectors, and key factors driving its rapid advancement, along with an overview of generative AI tools. Chapter 2 delves into large language models like ChatGPT, Google Gemini, Claude, Microsoft's Turing NLG, and Facebook's BlenderBot, exploring their integration with multimodal technologies and their effects on professional productivity. Chapter 3 offers a practical guide to mastering LLM prompting and customization, including tutorials on crafting effective prompts and advanced techniques, as well as real-world examples of AI applications. Chapter 4 examines how AI can enhance individual productivity, focusing on professional and personal benefits, ethical use, and future trends. Chapter 5 addresses data-driven decision- making, covering data analysis techniques, AI in trend identification, consumer behavior analysis, strategic planning, and product development. Chapter 6 discusses strategic and ethical considerations of AI, including AI feasibility, tool selection, multimodal workflows, and best practices for ethical AI development and deployment. Chapter 7 highlights the role of AI in transforming training and professional development, covering structured training programs, continuous learning initiatives, and fostering a culture of innovation and experimentation. Chapter 8 provides a guide to successfully implementing AI in organizations, discussing team composition, collaborative approaches, iterative development processes, and strategic alignment for AI initiatives. Finally, Chapter 9 looks ahead to the future of work, preparing readers for the AI revolution by addressing training and education, career paths, common fears, and future trends in the workforce. The primary audience for the book is professionals seeking to enhance productivity and organizations or businesses. For professionals, the book targets individuals from various industries, reflecting its aim to reach a broad audience across different professional fields. It is designed for employees at all levels, offering valuable insights to both newcomers to AI and seasoned professionals. Covering a range of topics from foundational concepts to advanced applications, the book is particularly relevant for those interested in improving efficiency, with a strong emphasis on practical applications and productivity tools to optimize work processes. For organizations and businesses, the book serves as a valuable resource for decision-makers and managers, especially with chapters on data-driven decision-making, strategic considerations, and AI implementation. HR and training professionals will find the focus on AI in training and development beneficial for talent management, while IT and technology teams will appreciate the information on AI tools and concepts.
Book Synopsis Annals of the Former World by : John McPhee
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 Synopsis Qualitative Data Analysis by : Ian Dey
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.
Download or read book Agility Shift written by Pamela Meyer and published by Routledge. This book was released on 2016-11-03 with total page 187 pages. Available in PDF, EPUB and Kindle. Book excerpt: As contrary as it sounds, "planning" -- as we traditionally understand the term--can be the worst thing a company can do. Consider that volatile weather events disrupt trusted supply chains, markets, and promised delivery schedules. Ever-shifting geo-political tensions, as well as internal political upheaval within U.S. and global governments, derail long-planned new ventures. Technology failures block opportunities. Competitors suddenly change their product or release date; your team cannot meet the pace of innovations in your market niche, leaving you sidelined. There are myriad ways in the current business environment for a company's well-considered business plans to go awry. Most business schools continue to prepare managers to be effective in stable and predictable environments, conditions that, if they ever existed at all, are long gone. The Agility Shift shows business leaders exactly how to make the radical mindset and strategy shift necessary to create an agile, entrepreneurial organization that can innovate and thrive in complex, ever-changing contexts. As author Pamela Meyer explains, there is much more involved than a reconfiguration of the org chart and job descriptions. It requires relinquishing the illusion of control at the very foundation of most management training and business practice. Despite most leaders' approaches, "Agility is not simply accelerated planning." Unlike many agility books on the market, The Agility Shift provides specific, actionable strategies and tactics for leaders at all levels of the organization to put into practice immediately to improve agility and achieve results.
Book Synopsis Transfer Learning for Natural Language Processing by : Paul Azunre
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 Synopsis Hands-On Q-Learning with Python by : Nazia Habib
Download or read book Hands-On Q-Learning with Python written by Nazia Habib and published by Packt Publishing Ltd. This book was released on 2019-04-19 with total page 200 pages. Available in PDF, EPUB and Kindle. Book excerpt: Leverage the power of reward-based training for your deep learning models with Python Key FeaturesUnderstand Q-learning algorithms to train neural networks using Markov Decision Process (MDP)Study practical deep reinforcement learning using Q-NetworksExplore state-based unsupervised learning for machine learning modelsBook Description Q-learning is a machine learning algorithm used to solve optimization problems in artificial intelligence (AI). It is one of the most popular fields of study among AI researchers. This book starts off by introducing you to reinforcement learning and Q-learning, in addition to helping you get familiar with OpenAI Gym as well as libraries such as Keras and TensorFlow. A few chapters into the book, you will gain insights into modelfree Q-learning and use deep Q-networks and double deep Q-networks to solve complex problems. This book will guide you in exploring use cases such as self-driving vehicles and OpenAI Gym’s CartPole problem. You will also learn how to tune and optimize Q-networks and their hyperparameters. As you progress, you will understand the reinforcement learning approach to solving real-world problems. You will also explore how to use Q-learning and related algorithms in real-world applications such as scientific research. Toward the end, you’ll gain a sense of what’s in store for reinforcement learning. By the end of this book, you will be equipped with the skills you need to solve reinforcement learning problems using Q-learning algorithms with OpenAI Gym, Keras, and TensorFlow. What you will learnExplore the fundamentals of reinforcement learning and the state-action-reward processUnderstand Markov decision processesGet well versed with libraries such as Keras, and TensorFlowCreate and deploy model-free learning and deep Q-learning agents with TensorFlow, Keras, and OpenAI GymChoose and optimize a Q-Network’s learning parameters and fine-tune its performanceDiscover real-world applications and use cases of Q-learningWho this book is for If you are a machine learning developer, engineer, or professional who wants to delve into the deep learning approach for a complex environment, then this is the book for you. Proficiency in Python programming and basic understanding of decision-making in reinforcement learning is assumed.
Book Synopsis The Delights of Learning Turkish by : Yasar Esendal Kuzucu
Download or read book The Delights of Learning Turkish written by Yasar Esendal Kuzucu and published by Createspace Independent Publishing Platform. This book was released on 2014-05-29 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Includes an answer key, a Turkish-English glossary, and an English-Turkish glossary.
Book Synopsis Python Reinforcement Learning by : Sudharsan Ravichandiran
Download or read book Python Reinforcement Learning written by Sudharsan Ravichandiran and published by Packt Publishing Ltd. This book was released on 2019-04-18 with total page 484 pages. Available in PDF, EPUB and Kindle. Book excerpt: Apply modern reinforcement learning and deep reinforcement learning methods using Python and its powerful libraries Key FeaturesYour entry point into the world of artificial intelligence using the power of PythonAn example-rich guide to master various RL and DRL algorithmsExplore the power of modern Python libraries to gain confidence in building self-trained applicationsBook Description Reinforcement Learning (RL) is the trending and most promising branch of artificial intelligence. This Learning Path will help you master not only the basic reinforcement learning algorithms but also the advanced deep reinforcement learning algorithms. The Learning Path starts with an introduction to RL followed by OpenAI Gym, and TensorFlow. You will then explore various RL algorithms, such as Markov Decision Process, Monte Carlo methods, and dynamic programming, including value and policy iteration. You'll also work on various datasets including image, text, and video. This example-rich guide will introduce you to deep RL algorithms, such as Dueling DQN, DRQN, A3C, PPO, and TRPO. You will gain experience in several domains, including gaming, image processing, and physical simulations. You'll explore TensorFlow and OpenAI Gym to implement algorithms that also predict stock prices, generate natural language, and even build other neural networks. You will also learn about imagination-augmented agents, learning from human preference, DQfD, HER, and many of the recent advancements in RL. By the end of the Learning Path, you will have all the knowledge and experience needed to implement RL and deep RL in your projects, and you enter the world of artificial intelligence to solve various real-life problems. This Learning Path includes content from the following Packt products: Hands-On Reinforcement Learning with Python by Sudharsan RavichandiranPython Reinforcement Learning Projects by Sean Saito, Yang Wenzhuo, and Rajalingappaa ShanmugamaniWhat you will learnTrain an agent to walk using OpenAI Gym and TensorFlowSolve multi-armed-bandit problems using various algorithmsBuild intelligent agents using the DRQN algorithm to play the Doom gameTeach your agent to play Connect4 using AlphaGo ZeroDefeat Atari arcade games using the value iteration methodDiscover how to deal with discrete and continuous action spaces in various environmentsWho this book is for If you’re an ML/DL enthusiast interested in AI and want to explore RL and deep RL from scratch, this Learning Path is for you. Prior knowledge of linear algebra is expected.
Book Synopsis Transformer Condition Control by : Vasily Ya. Ushakov
Download or read book Transformer Condition Control written by Vasily Ya. Ushakov and published by Springer Nature. This book was released on 2021-09-01 with total page 150 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is devoted to one of the main problems of modern electrical power engineering—power transformer diagnostics. The first three chapters discuss the fundamentals: The first chapter presents the physical reasons for power transformers’ failures and the technical and economic consequences of disruption of the normal operation. The second chapter reviews the standard technologies for monitoring the state of the high-voltage transformers. The third chapter tells about monitoring the condition of transformer windings based on the pulse method. The fourth chapter presents the technologies for transformer windings condition controlled by means of nanosecond pulses. The stages of improving the pulsed method based on a short probing pulse of the nanosecond range, the results of experiments on identifying the radial and axial displacements of the winding, studies of the effect of the duration and shape of the probing pulse on the sensitivity of the diagnostic procedure, and the stages of developing a mathematical as well as physical model of a power transformer are consistently presented.
Book Synopsis Probabilistic Machine Learning by : Kevin P. Murphy
Download or read book Probabilistic Machine Learning written by Kevin P. Murphy and published by MIT Press. This book was released on 2022-03-01 with total page 858 pages. Available in PDF, EPUB and Kindle. Book excerpt: A detailed and up-to-date introduction to machine learning, presented through the unifying lens of probabilistic modeling and Bayesian decision theory. This book offers a detailed and up-to-date introduction to machine learning (including deep learning) through the unifying lens of probabilistic modeling and Bayesian decision theory. The book covers mathematical background (including linear algebra and optimization), basic supervised learning (including linear and logistic regression and deep neural networks), as well as more advanced topics (including transfer learning and unsupervised learning). End-of-chapter exercises allow students to apply what they have learned, and an appendix covers notation. Probabilistic Machine Learning grew out of the author’s 2012 book, Machine Learning: A Probabilistic Perspective. More than just a simple update, this is a completely new book that reflects the dramatic developments in the field since 2012, most notably deep learning. In addition, the new book is accompanied by online Python code, using libraries such as scikit-learn, JAX, PyTorch, and Tensorflow, which can be used to reproduce nearly all the figures; this code can be run inside a web browser using cloud-based notebooks, and provides a practical complement to the theoretical topics discussed in the book. This introductory text will be followed by a sequel that covers more advanced topics, taking the same probabilistic approach.
