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Название: Python Development with Large Language Models: From Text to Tasks: Python Programming with the Help of Large Language Models! 5 Projects to Master Python Development with Large Language Models
Автор: Katie Millie
Издательство: Independently published
Серия: Python Trailblazer’s Bible
Год: 2024
Страниц: 163
Язык: английский
Формат: pdf
Размер: 23.2 MB

Unchain Your Coding Potential: Python Development with Large Language Models. Is your Python code stuck in the dark ages?Are you tired of repetitive tasks and endless syntax errors? Break free from the shackles of manual coding with the revolutionary power of Large Language Models (LLMs)! Python Development with Large Language Models is your launchpad into the future of programming. This book equips you with the knowledge and tools to supercharge your Python development by leveraging the incredible capabilities of LLMs. The magic behind LLMs: Demystify the technology and discover how these powerful language models process, analyze, and generate text. Essential Python libraries and frameworks: Learn to leverage popular tools like TensorFlow or PyTorch, the bridges connecting LLMs and Python development. Practical techniques for LLM integration: Explore how to access and interact with LLMs, process text data effectively, and fine-tune them for specific tasks within your projects. Real-world project implementation: Put your knowledge into action by building a practical application that utilizes LLMs in your Python development environment. Ready to unlock the true potential of your Python coding? Don't wait! Buy Python Development with Large Language Models today and launch yourself into the future of coding! This comprehensive guide will equip you with the knowledge and tools to transform your Python development workflow and become a true coding master. Take control of your programming destiny.
Разместил: Ingvar16 13-05-2024, 12:27 | Комментарии: 0 | Подробнее
Python Programmierung Tipps und Projekte - Mai 2024Название: Python Programmierung Tipps und Projekte - Mai 2024
Автор: Papercut Ltd
Издательство: Papercut Ltd
Год / месяц: Mai 2024
Страниц: 148
Формат: PDF
Размер: 111 MB
Язык: Deutsch/немецкий

Python Programmierung Tipps und Projekte - это идеальное цифровое издание для пользователей, которые хотят поднять свои навыки на новый уровень. Вы хотите улучшить свой пользовательский опыт или получить инсайдерские знания? Вы хотите учиться непосредственно у экспертов в этой области? Хотите узнать бесчисленные сокращения, которыми пользуются профессионалы? На страницах этого нового руководства для продвинутых пользователей вы узнаете все, что нужно, чтобы стать более уверенным, знающим и опытным пользователем, который будет извлекать максимальную пользу из своего кодирования и, в конечном счете, из самого программирования Python. С этим неофициальным руководством у вас никогда не возникнет проблем или вопросов, которые вы не сможете решить, изучая, осваивая и совершенствуя свои навыки программирования на языке Python.
Разместил: Dovegone 13-05-2024, 00:13 | Комментарии: 0 | Подробнее
Название: TensorFlow Developer Certification Guide: Crack Google’s official exam on getting skilled with managing production-grade ML models
Автор: Patrick J
Издательство: GitforGits
Год: 2023
Страниц: 212
Язык: английский
Формат: pdf, azw3, epub, mobi
Размер: 10.1 MB

Designed with both beginners and professionals in mind, the book is meticulously structured to cover a broad spectrum of concepts, applications, and hands-on practices that form the core of the TensorFlow Developer Certificate exam. Starting with foundational concepts, the book guides you through the fundamental aspects of TensorFlow, Machine Learning algorithms, and Deep Learning models. The initial chapters focus on data preprocessing, exploratory analysis, and essential tools required for building robust models. The book then delves into Convolutional Neural Networks (CNNs), Long Short-Term Memory Networks (LSTMs), and advanced neural network techniques such as GANs and Transformer Architecture. Emphasizing practical application, each chapter is peppered with detailed explanations, code snippets, and real-world examples, allowing you to apply the concepts in various domains such as text classification, sentiment analysis, object detection, and more. A distinctive feature of the book is its focus on various optimization and regularization techniques that enhance model performance. As the book progresses, it navigates through the complexities of deploying TensorFlow models into production. It includes exhaustive sections on TensorFlow Serving, Kubernetes Cluster, and edge computing with TensorFlow Lite. The book provides practical insights into monitoring, updating, and handling possible errors in production, ensuring a smooth transition from development to deployment. The final chapters are devoted to preparing you for the TensorFlow Developer Certificate exam. From strategies, tips, and coding challenges to a summary of the entire learning journey, these sections serve as a robust toolkit for exam readiness. With hints and solutions provided for challenges, you can assess your knowledge and fine-tune your problem solving skills.
Разместил: Ingvar16 12-05-2024, 21:31 | Комментарии: 0 | Подробнее
Название: The Python For Finance Handbook: Unlocking Financial Insights with Python
Автор: Hayden Van Der Post, Vincent Bisette
Издательство: Reactive Publishing
Год: 2024
Страниц: 583
Язык: английский
Формат: pdf, epub, mobi
Размер: 10.1 MB

Dive into the dynamic world of finance armed with the power of Python! In 'The Python for Finance Handbook,' embark on a journey where financial expertise meets cutting-edge technology. This comprehensive guide equips you with the essential tools and techniques to leverage Python programming for financial analysis, modeling, and decision-making. From mastering data manipulation to implementing advanced statistical methods, this handbook demystifies complex financial concepts through practical examples and real-world applications. Whether you're a seasoned finance professional or a newcomer to the field, this book empowers you to harness Python's versatility to streamline processes, gain insights, and make informed investment decisions. Explore key topics such as portfolio optimization, risk management, algorithmic trading, and more, as you discover how Python revolutionizes traditional finance practices. With step-by-step instructions, code snippets, and hands-on exercises, 'The Python for Finance Handbook' is your indispensable companion for navigating the intersection of finance and technology. Elevate your financial prowess and stay ahead in today's rapidly evolving financial landscape with Python as your guide. Python's simplicity and readability have made it particularly attractive for finance professionals who are not primarily programmers but require a tool that can extend their analytical capabilities without a steep learning curve. The language's syntax is intuitive and emphasizes readability, which facilitates easier maintenance and collaboration among professionals from various disciplines.
Разместил: Ingvar16 12-05-2024, 18:46 | Комментарии: 0 | Подробнее
Название: Software Engineering and Management: Theory and Application: Volume 16
Автор: Roger Lee
Издательство: Springer
Серия: Studies in Computational Intelligence
Год: 2024
Страниц: 238
Язык: английский
Формат: pdf (true), epub
Размер: 31.9 MB

The book reports state of the art results in Software Engineering Research, Management & Applications in both printed and electronic form. SCI (Studies in Computation Intelligence) has grown into the most comprehensive computational intelligence research forum available in the world. Federated Leaning (FL), as a distributed Machine Learning paradigm, enables the collaboration of a group of agents to collaboratively conduct a learning model training, while preserving the data privacy. Federated Learning is viable distributed Machine Learning framework that can be applied to different smart-world systems, supported by the advancement of rapidly growing networking and computing techniques. Federated Learning (FL) has made possible the collaborative training of Machine Learning models between aggregation server and clients without sharing their private data. With the massive volume of heterogeneous data from various clients, the server faces challenges such as data unbalance, data corruption, and/or data irrelevancy. As a result, the FL setting is exposed to numerous security risks that lead to performance deterioration of learning effectiveness. To tackle the issue, in this paper we propose the Heterogeneity Index Based Clustering (HIC) approach, which enables the dynamic categorization of clients into clusters. Particularly, the model weights are dynamically clustered based on their heterogeneity level using an affinity propagation method. The HIC approach uses a simple, but effective way of scaling data heterogeneity and dynamic clustering to create a resilient learning system against backdoor attacks that outperforms the existing works on FL robustness.
Разместил: Ingvar16 12-05-2024, 15:24 | Комментарии: 0 | Подробнее
Название: Exploration of Artificial Intelligence and Blockchain Technology in Smart and Secure Healthcare
Автор: Arvind K. Sharma, Dalip Kamboj, Savita Wadhawan, Gousia Habib
Издательство: Bentham Books
Серия: Advances in Computing Communications and Informatics
Год: 2024
Страниц: 316
Язык: английский
Формат: pdf (true), epub
Размер: 18.4 MB

This book offers in-depth reviews of different techniques and novel approaches of using blockchain and Artificial Intelligence (AI) in smart healthcare services. The volume brings 14 reviews and research articles written by academicians, researchers and industry professionals to give readers a current perspective of smart healthcare solutions for medical and public health services. From the last decade onward, a considerable amount of research and developments in technology have taken place especially in the healthcare industry, with the involvement of technologies like Artificial Intelligence (AI), Machine Learning (ML), Deep Learning, Blockchain, Communication Systems, Internet of Things, Multisensory Systems, etc. The purpose is only to make smart and secure healthcare possible. Machine Learning techniques and algorithms are required to give a boost to the aim of smart healthcare. Hence, to fulfill the vision of smart healthcare, the tools and applications based on Artificial Intelligence and Machine Learning are becoming extremely popular for producing more accuracy (in terms of values) in predicting results (without being explicitly programmed) in the healthcare industry. However, Artificial Intelligence-based algorithms are quite helpful for the transformation of physiological data into clinical information of real values, but for processing such big data from a set of medical images and identifying or extracting characteristic patterns of health function, then translating these patterns into clinical information definitely requires an adequate knowledge base of physiology, advanced digital signal processing capabilities, and Machine Learning.
Разместил: Ingvar16 12-05-2024, 06:49 | Комментарии: 0 | Подробнее
Название: Deep Learning Tools for Predicting Stock Market Movements
Автор: Renuka Sharma, Kiran Mehta
Издательство: Wiley-Scrivener
Год: 2024
Страниц: 489
Язык: английский
Формат: pdf (true), epub
Размер: 14,5 MB

The book provides a comprehensive overview of current research and developments in the field of Deep Learning models for stock market forecasting in the developed and developing worlds. The book delves into the realm of Deep Learning and embraces the challenges, opportunities, and transformation of stock market analysis. Deep Learning helps foresee market trends with increased accuracy. With advancements in Deep Learning, new opportunities in styles, tools, and techniques evolve and embrace data-driven insights with theories and practical applications. Learn about designing, training, and applying predictive models with rigorous attention to detail. This book offers critical thinking skills and the cultivation of discerning approaches to market analysis. The present study gives a comprehensive overview of the advancements and potential avenues in the realm of utilizing Deep Learning techniques for forecasting stock market trends. This study surveys the evolving landscape of Deep Learning methodologies employed in predicting stock price movements and offers insights into their effectiveness across various time frames and market conditions. The research delves into the multifaceted aspects of this field, encompassing architectures such as recurrent neural networks (RNNs), convolutional neural networks (CNNs), and more recent transformer-based models.
Разместил: Ingvar16 12-05-2024, 06:12 | Комментарии: 0 | Подробнее
Название: Dependable Computing: Design and Assessment
Автор: Ravishankar K. Iyer, Zbigniew T. Kalbarczyk, Nithin M. Nakka
Издательство: Wiley-IEEE Press
Год: 2024
Страниц: 851
Язык: английский
Формат: pdf (true), epub
Размер: 24.5 MB

Covering dependability from software and hardware perspectives. Dependable Computing: Design and Assessment looks at both the software and hardware aspects of dependability. This book is suitable for those studying in the fields of computer engineering and Computer Science. Professionals who are working within the new reality to ensure dependable computing will find helpful information to support their efforts. With the support of practical case studies and use cases from both academia and real-world deployments, the book provides a journey of developments that include the impact of Artificial Intelligence and Machine Learning on this ever-growing field. This book offers a single compendium that spans the myriad areas in which dependability has been applied, providing theoretical concepts and applied knowledge with content that will excite a beginner, and rigor that will satisfy an expert. Accompanying the book is an online repository of problem sets and solutions, as well as slides for instructors, that span the chapters of the book.
Разместил: Ingvar16 12-05-2024, 05:26 | Комментарии: 0 | Подробнее
Название: Artificial Intelligence for Learning: Using AI and Generative AI to Support Learner Development, 2nd Edition
Автор: Donald Clark
Издательство: Kogan Page
Год: 2024
Страниц: 313
Язык: английский
Формат: pdf (true), epub
Размер: 22.7 MB

With Artificial Intelligence (AI) creating huge opportunities for learning and employee development, how can learning professionals best implement the use of AI into their environment? Artificial Intelligence for Learning is the essential guide for learning professionals who want to understand how to use AI to improve all aspects of learning in organizations. This new edition debunks the myths and misconceptions around AI, discusses the learning theory behind generative AI and gives strategic and practical advice on how AI can be used. This book also includes specific guidance on how AI can provide learning support, chatbot functionality and content, as well as ideas on ethics and personalization. This book is necessary reading for all learning practitioners needing to understand AI and what it means in practice. AI in one sense means doing what humans do when they learn. The AI field is thick with references to ‘learning’, the most common being machine, deep and reinforcement learning. Machine Learning uses algorithms and statistical models and applies patterns and inferences to perform tasks through experience. This is analogous to traditional learning through exposure to taught experiences. Deep Learning is a Machine Learning technique that uses layered neural networks with large datasets, supervised, semi-supervised or unsupervised, to perform tasks. This is more like learning from the real world to gain competence and solve actual problems. Reinforcement learning operates on maximizing reward by exposure to existing knowledge and exploring new knowledge.
Разместил: Ingvar16 12-05-2024, 04:40 | Комментарии: 0 | Подробнее
Название: Computability and Complexity: Foundations and Tools for Pursuing Scientific Applications
Автор: Rod Downey
Издательство: Springer
Серия: Undergraduate Topics in Computer Science
Год: 2024
Страниц: 361
Язык: английский
Формат: pdf (true), epub
Размер: 10.1 MB

This is a book about computation, something which is ubiquitous in the modern world. More precisely, it examines computability theory and computational complexity theory. Computability theory is the part of mathematics and Computer Science which seeks to clarify what we mean by computation or algorithm. When is there a computational solution possible to some question? How can we show that none is possible? How computationally hard is the question we are concerned with? Arguably, this area lead to the development of digital computers. (Computational) complexity theory is an intellectual heir of computability theory. Complexity theory is concerned with understanding what resources are needed for computation, where typically we would measure the resources in terms of time and space. Can we perform some task in a feasible number of steps? Can we perform some algorithm with only a limited memory? Does randomness help? Are there standard approaches to overcoming computational difficulty?
Разместил: Ingvar16 11-05-2024, 20:13 | Комментарии: 0 | Подробнее

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