The Language Architect Building The Future With Mistral Llm
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The Language Architect Building The Future With Mistral Llm
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Author : Anand Vemula
language : en
Publisher: Anand Vemula
Release Date :
The Language Architect Building The Future With Mistral Llm written by Anand Vemula and has been published by Anand Vemula this book supported file pdf, txt, epub, kindle and other format this book has been release on with Computers categories.
The Language Architect: Building the Future with Mistral LLM Unlock the potential of language and co-create the future with Mistral LLM, a revolutionary large language model. In "The Language Architect: Building the Future with Mistral LLM," you'll embark on a journey into the exciting world of large language models (LLMs) and delve into the capabilities of Mistral LLM, a powerful AI tool that's shaping the future of communication. This book is your comprehensive guide to understanding Mistral LLM. You'll explore its inner workings, from its innovative architecture to its impressive multilingual abilities. Master the Fundamentals: Gain a solid understanding of LLMs and how they revolutionize human-computer interaction. Dive into Mistral LLM: Explore the technical aspects of Mistral, including its decoder-only transformer model, efficiency techniques, and training processes. Unleash the Power of Words: Discover how Mistral LLM can generate creative text formats, translate languages with accuracy, and answer your questions in informative ways. Become a Language Architect: Learn how to leverage Mistral LLM for various applications, from crafting compelling content to creating chatbots and virtual assistants. But "The Language Architect" goes beyond just technical understanding. It emphasizes the responsible development and use of LLMs. Navigate Ethical Considerations: Explore the potential biases and limitations of LLMs and how Mistral prioritizes safety and ethical AI practices. Forge a Human-Machine Partnership: Discover how to collaborate with Mistral LLM to achieve exceptional results while ensuring responsible use of this powerful technology. This book is for anyone interested in the future of language and AI. Whether you're a writer, programmer, entrepreneur, or simply curious about technological advancements, "The Language Architect" equips you with the knowledge and insights to become a co-architect of the future, working alongside Mistral LLM to unlock its potential for positive change.
Artificial Intelligence With Python Cookbook
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Author : Ben Auffarth
language : en
Publisher: Packt Publishing Ltd
Release Date : 2020-10-30
Artificial Intelligence With Python Cookbook written by Ben Auffarth and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-10-30 with Computers categories.
Work through practical recipes to learn how to solve complex machine learning and deep learning problems using Python Key FeaturesGet up and running with artificial intelligence in no time using hands-on problem-solving recipesExplore popular Python libraries and tools to build AI solutions for images, text, sounds, and imagesImplement NLP, reinforcement learning, deep learning, GANs, Monte-Carlo tree search, and much moreBook Description Artificial intelligence (AI) plays an integral role in automating problem-solving. This involves predicting and classifying data and training agents to execute tasks successfully. This book will teach you how to solve complex problems with the help of independent and insightful recipes ranging from the essentials to advanced methods that have just come out of research. Artificial Intelligence with Python Cookbook starts by showing you how to set up your Python environment and taking you through the fundamentals of data exploration. Moving ahead, you’ll be able to implement heuristic search techniques and genetic algorithms. In addition to this, you'll apply probabilistic models, constraint optimization, and reinforcement learning. As you advance through the book, you'll build deep learning models for text, images, video, and audio, and then delve into algorithmic bias, style transfer, music generation, and AI use cases in the healthcare and insurance industries. Throughout the book, you’ll learn about a variety of tools for problem-solving and gain the knowledge needed to effectively approach complex problems. By the end of this book on AI, you will have the skills you need to write AI and machine learning algorithms, test them, and deploy them for production. What you will learnImplement data preprocessing steps and optimize model hyperparametersDelve into representational learning with adversarial autoencodersUse active learning, recommenders, knowledge embedding, and SAT solversGet to grips with probabilistic modeling with TensorFlow probabilityRun object detection, text-to-speech conversion, and text and music generationApply swarm algorithms, multi-agent systems, and graph networksGo from proof of concept to production by deploying models as microservicesUnderstand how to use modern AI in practiceWho this book is for This AI machine learning book is for Python developers, data scientists, machine learning engineers, and deep learning practitioners who want to learn how to build artificial intelligence solutions with easy-to-follow recipes. You’ll also find this book useful if you’re looking for state-of-the-art solutions to perform different machine learning tasks in various use cases. Basic working knowledge of the Python programming language and machine learning concepts will help you to work with code effectively in this book.
Machine Learning For Time Series With Python
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Author : Ben Auffarth
language : en
Publisher: Packt Publishing Ltd
Release Date : 2021-10-29
Machine Learning For Time Series With Python written by Ben Auffarth and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-10-29 with Computers categories.
Get better insights from time-series data and become proficient in model performance analysis Key FeaturesExplore popular and modern machine learning methods including the latest online and deep learning algorithmsLearn to increase the accuracy of your predictions by matching the right model with the right problemMaster time series via real-world case studies on operations management, digital marketing, finance, and healthcareBook Description The Python time-series ecosystem is huge and often quite hard to get a good grasp on, especially for time-series since there are so many new libraries and new models. This book aims to deepen your understanding of time series by providing a comprehensive overview of popular Python time-series packages and help you build better predictive systems. Machine Learning for Time-Series with Python starts by re-introducing the basics of time series and then builds your understanding of traditional autoregressive models as well as modern non-parametric models. By observing practical examples and the theory behind them, you will become confident with loading time-series datasets from any source, deep learning models like recurrent neural networks and causal convolutional network models, and gradient boosting with feature engineering. This book will also guide you in matching the right model to the right problem by explaining the theory behind several useful models. You'll also have a look at real-world case studies covering weather, traffic, biking, and stock market data. By the end of this book, you should feel at home with effectively analyzing and applying machine learning methods to time-series. What you will learnUnderstand the main classes of time series and learn how to detect outliers and patternsChoose the right method to solve time-series problemsCharacterize seasonal and correlation patterns through autocorrelation and statistical techniquesGet to grips with time-series data visualizationUnderstand classical time-series models like ARMA and ARIMAImplement deep learning models, like Gaussian processes, transformers, and state-of-the-art machine learning modelsBecome familiar with many libraries like Prophet, XGboost, and TensorFlowWho this book is for This book is ideal for data analysts, data scientists, and Python developers who want instantly useful and practical recipes to implement today, and a comprehensive reference book for tomorrow. Basic knowledge of the Python Programming language is a must, while familiarity with statistics will help you get the most out of this book.
Driving Digital Strategy
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Author : Sunil Gupta
language : en
Publisher: Harvard Business Press
Release Date : 2018-07-24
Driving Digital Strategy written by Sunil Gupta and has been published by Harvard Business Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-07-24 with Computers categories.
Digital transformation is no longer news--it's a necessity. Despite the widespread threat of disruption, many large companies in traditional industries have succeeded at digitizing their businesses in truly transformative ways. The New York Times, formerly a bastion of traditional media, has created a thriving digital product behind a carefully designed paywall. Best Buy has transformed its business in the face of Amazon's threat. John Deere has formed a data-analysis arm to complement its farm-equipment business. And Goldman Sachs and many others are using digital technologies to reimagine their businesses. In Driving Digital Strategy, Harvard Business School professor Sunil Gupta provides an actionable framework for following their lead. For over a decade, Gupta has studied digital transformation at Fortune 500 companies. He knows what works and what doesn't. Merely dabbling in digital or launching a small independent unit, which many companies do, will not bring success. Instead you need to fundamentally change the core of your business and ensure that your digital strategy touches all aspects of your organization: your business model, value chain, customer relationships, and company culture. Gupta covers each aspect in vivid detail while providing navigation tips and best practices along the way. Filled with rich and illuminating case studies of companies at the forefront of digital transformation, Driving Digital Strategy is the comprehensive guide you need to take full advantage of the limitless opportunities the digital age provides.
Rise Of The Data Cloud
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Author : Frank Slootman
language : en
Publisher: AuthorHouse
Release Date : 2020-12-18
Rise Of The Data Cloud written by Frank Slootman and has been published by AuthorHouse this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-12-18 with Business & Economics categories.
The rise of the Data Cloud is ushering in a new era of computing. The world’s digital data is mass migrating to the cloud, where it can be more effectively integrated, managed, and mobilized. The data cloud eliminates data siloes and enables data sharing with business partners, capitalizing on data network effects. It democratizes data analytics, making the most sophisticated data science tools accessible to organizations of all sizes. Data exchanges enable businesses to discover, explore, and easily purchase or sell data—opening up new revenue streams. Business leaders have long dreamed of data driving their organizations. Now, thanks to the Data Cloud, nothing stands in their way.
Natural Language Processing With Transformers Revised Edition
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Author : Lewis Tunstall
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2022-05-26
Natural Language Processing With Transformers Revised Edition written by Lewis Tunstall and has been published by "O'Reilly Media, Inc." this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-05-26 with Computers categories.
Since their introduction in 2017, transformers have quickly become the dominant architecture for achieving state-of-the-art results on a variety of natural language processing tasks. If you're a data scientist or coder, this practical book -now revised in full color- shows you how to train and scale these large models using Hugging Face Transformers, a Python-based deep learning library. Transformers have been used to write realistic news stories, improve Google Search queries, and even create chatbots that tell corny jokes. In this guide, authors Lewis Tunstall, Leandro von Werra, and Thomas Wolf, among the creators of Hugging Face Transformers, use a hands-on approach to teach you how transformers work and how to integrate them in your applications. You'll quickly learn a variety of tasks they can help you solve. Build, debug, and optimize transformer models for core NLP tasks, such as text classification, named entity recognition, and question answering Learn how transformers can be used for cross-lingual transfer learning Apply transformers in real-world scenarios where labeled data is scarce Make transformer models efficient for deployment using techniques such as distillation, pruning, and quantization Train transformers from scratch and learn how to scale to multiple GPUs and distributed environments
Realizing The Abidjan Principles On The Right To Education
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Author : Frank Adamson
language : en
Publisher: Edward Elgar Publishing
Release Date : 2021-05-28
Realizing The Abidjan Principles On The Right To Education written by Frank Adamson and has been published by Edward Elgar Publishing this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-05-28 with Political Science categories.
This insightful book analyses the process of the first adoption of guiding human rights principles for education, the Abidjan Principles. It explains the development of the Abidjan Principles, including their articulation of the right to education, the state obligation to provide quality public education, and the role of private actors in education.
How To Make A Spaceship
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Author : Julian Guthrie
language : en
Publisher: Penguin
Release Date : 2016-09-20
How To Make A Spaceship written by Julian Guthrie and has been published by Penguin this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-09-20 with Biography & Autobiography categories.
A New York Times bestseller! The historic race that reawakened the promise of manned spaceflight A Finalist for the PEN/E. O. Wilson Literary Science Writing Award Alone in a Spartan black cockpit, test pilot Mike Melvill rocketed toward space. He had eighty seconds to exceed the speed of sound and begin the climb to a target no civilian pilot had ever reached. He might not make it back alive. If he did, he would make history as the world’s first commercial astronaut. The spectacle defied reason, the result of a competition dreamed up by entrepreneur Peter Diamandis, whose vision for a new race to space required small teams to do what only the world’s largest governments had done before. Peter Diamandis was the son of hardworking immigrants who wanted their science prodigy to make the family proud and become a doctor. But from the age of eight, when he watched Apollo 11 land on the Moon, his singular goal was to get to space. When he realized NASA was winding down manned space flight, Diamandis set out on one of the great entrepreneurial adventure stories of our time. If the government wouldn’t send him to space, he would create a private space flight industry himself. In the 1990s, this idea was the stuff of science fiction. Undaunted, Diamandis found inspiration in an unlikely place: the golden age of aviation. He discovered that Charles Lindbergh made his transatlantic flight to win a $25,000 prize. The flight made Lindbergh the most famous man on earth and galvanized the airline industry. Why, Diamandis thought, couldn’t the same be done for space flight? The story of the bullet-shaped SpaceShipOne, and the other teams in the hunt, is an extraordinary tale of making the impossible possible. It is driven by outsized characters—Burt Rutan, Richard Branson, John Carmack, Paul Allen—and obsessive pursuits. In the end, as Diamandis dreamed, the result wasn’t just a victory for one team; it was the foundation for a new industry and a new age.
Eloquent Ruby
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Author : Russ Olsen
language : en
Publisher: Addison-Wesley Professional
Release Date : 2011-02-07
Eloquent Ruby written by Russ Olsen and has been published by Addison-Wesley Professional this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-02-07 with Computers categories.
It’s easy to write correct Ruby code, but to gain the fluency needed to write great Ruby code, you must go beyond syntax and absorb the “Ruby way” of thinking and problem solving. In Eloquent Ruby, Russ Olsen helps you write Ruby like true Rubyists do–so you can leverage its immense, surprising power. Olsen draws on years of experience internalizing the Ruby culture and teaching Ruby to other programmers. He guides you to the “Ah Ha!” moments when it suddenly becomes clear why Ruby works the way it does, and how you can take advantage of this language’s elegance and expressiveness. Eloquent Ruby starts small, answering tactical questions focused on a single statement, method, test, or bug. You’ll learn how to write code that actually looks like Ruby (not Java or C#); why Ruby has so many control structures; how to use strings, expressions, and symbols; and what dynamic typing is really good for. Next, the book addresses bigger questions related to building methods and classes. You’ll discover why Ruby classes contain so many tiny methods, when to use operator overloading, and when to avoid it. Olsen explains how to write Ruby code that writes its own code–and why you’ll want to. He concludes with powerful project-level features and techniques ranging from gems to Domain Specific Languages. A part of the renowned Addison-Wesley Professional Ruby Series, Eloquent Ruby will help you “put on your Ruby-colored glasses” and get results that make you a true believer.
Deep Learning In Natural Language Processing
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Author : Li Deng
language : en
Publisher: Springer
Release Date : 2018-05-23
Deep Learning In Natural Language Processing written by Li Deng and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-05-23 with Computers categories.
In recent years, deep learning has fundamentally changed the landscapes of a number of areas in artificial intelligence, including speech, vision, natural language, robotics, and game playing. In particular, the striking success of deep learning in a wide variety of natural language processing (NLP) applications has served as a benchmark for the advances in one of the most important tasks in artificial intelligence. This book reviews the state of the art of deep learning research and its successful applications to major NLP tasks, including speech recognition and understanding, dialogue systems, lexical analysis, parsing, knowledge graphs, machine translation, question answering, sentiment analysis, social computing, and natural language generation from images. Outlining and analyzing various research frontiers of NLP in the deep learning era, it features self-contained, comprehensive chapters written by leading researchers in the field. A glossary of technical terms and commonly used acronyms in the intersection of deep learning and NLP is also provided. The book appeals to advanced undergraduate and graduate students, post-doctoral researchers, lecturers and industrial researchers, as well as anyone interested in deep learning and natural language processing.