Machine Learning Algorithms Using Scikit and TensorFlow Environments PDF Download
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Author: Baby Maruthi, Puvvadi
Publisher: IGI Global
ISBN: 1668485338
Category : Computers
Languages : en
Pages : 473
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Book Description
Machine learning is able to solve real-time problems. It has several algorithms such as classification, clustering, and more. To learn these essential algorithms, we require tools like Scikit and TensorFlow. Machine Learning Algorithms Using Scikit and TensorFlow Environments assists researchers in learning and implementing these critical algorithms. Covering key topics such as classification, artificial neural networks, prediction, random forest, and regression analysis, this premier reference source is ideal for industry professionals, computer scientists, researchers, academicians, scholars, practitioners, instructors, and students.
Author: Baby Maruthi, Puvvadi
Publisher: IGI Global
ISBN: 1668485338
Category : Computers
Languages : en
Pages : 473
Get Book Here
Book Description
Machine learning is able to solve real-time problems. It has several algorithms such as classification, clustering, and more. To learn these essential algorithms, we require tools like Scikit and TensorFlow. Machine Learning Algorithms Using Scikit and TensorFlow Environments assists researchers in learning and implementing these critical algorithms. Covering key topics such as classification, artificial neural networks, prediction, random forest, and regression analysis, this premier reference source is ideal for industry professionals, computer scientists, researchers, academicians, scholars, practitioners, instructors, and students.
Author: Baby Maruthi
Publisher:
ISBN: 9781668485354
Category :
Languages : en
Pages : 0
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Book Description
Author: Sebastian Raschka
Publisher: Packt Publishing Ltd
ISBN: 1801816387
Category : Computers
Languages : en
Pages : 775
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Book Description
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.
Author: Aurélien Géron
Publisher: "O'Reilly Media, Inc."
ISBN: 149203259X
Category : Computers
Languages : en
Pages : 830
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Book Description
Through a series of recent breakthroughs, deep learning has boosted the entire field of machine learning. Now, even programmers who know close to nothing about this technology can use simple, efficient tools to implement programs capable of learning from data. This practical book shows you how. By using concrete examples, minimal theory, and two production-ready Python frameworks—Scikit-Learn and TensorFlow—author Aurélien Géron helps you gain an intuitive understanding of the concepts and tools for building intelligent systems. You’ll learn a range of techniques, starting with simple linear regression and progressing to deep neural networks. With exercises in each chapter to help you apply what you’ve learned, all you need is programming experience to get started. Explore the machine learning landscape, particularly neural nets Use Scikit-Learn to track an example machine-learning project end-to-end Explore several training models, including support vector machines, decision trees, random forests, and ensemble methods Use the TensorFlow library to build and train neural nets Dive into neural net architectures, including convolutional nets, recurrent nets, and deep reinforcement learning Learn techniques for training and scaling deep neural nets
Author: Sebastian Raschka
Publisher: Packt Publishing Ltd
ISBN: 1783555149
Category : Computers
Languages : en
Pages : 455
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Book Description
Unlock deeper insights into Machine Leaning with this vital guide to cutting-edge predictive analytics About This Book Leverage Python's most powerful open-source libraries for deep learning, data wrangling, and data visualization Learn effective strategies and best practices to improve and optimize machine learning systems and algorithms Ask – and answer – tough questions of your data with robust statistical models, built for a range of datasets Who This Book Is For If you want to find out how to use Python to start answering critical questions of your data, pick up Python Machine Learning – whether you want to get started from scratch or want to extend your data science knowledge, this is an essential and unmissable resource. What You Will Learn Explore how to use different machine learning models to ask different questions of your data Learn how to build neural networks using Keras and Theano Find out how to write clean and elegant Python code that will optimize the strength of your algorithms Discover how to embed your machine learning model in a web application for increased accessibility Predict continuous target outcomes using regression analysis Uncover hidden patterns and structures in data with clustering Organize data using effective pre-processing techniques Get to grips with sentiment analysis to delve deeper into textual and social media data In Detail Machine learning and predictive analytics are transforming the way businesses and other organizations operate. Being able to understand trends and patterns in complex data is critical to success, becoming one of the key strategies for unlocking growth in a challenging contemporary marketplace. Python can help you deliver key insights into your data – its unique capabilities as a language let you build sophisticated algorithms and statistical models that can reveal new perspectives and answer key questions that are vital for success. Python Machine Learning gives you access to the world of predictive analytics and demonstrates why Python is one of the world's leading data science languages. If you want to ask better questions of data, or need to improve and extend the capabilities of your machine learning systems, this practical data science book is invaluable. Covering a wide range of powerful Python libraries, including scikit-learn, Theano, and Keras, and featuring guidance and tips on everything from sentiment analysis to neural networks, you'll soon be able to answer some of the most important questions facing you and your organization. Style and approach Python Machine Learning connects the fundamental theoretical principles behind machine learning to their practical application in a way that focuses you on asking and answering the right questions. It walks you through the key elements of Python and its powerful machine learning libraries, while demonstrating how to get to grips with a range of statistical models.
Author: Barbosa, Belem
Publisher: IGI Global
ISBN:
Category : Business & Economics
Languages : en
Pages : 490
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Book Description
In today's fast-paced global marketplace, businesses grapple with the relentless demand for innovation in marketing strategies. The landscape is ever-evolving, driven by digital advancements and shifting consumer behaviors, leaving companies scrambling to stay relevant. Academic scholars, educators, and managers face a formidable challenge: deciphering the complex web of trends and technologies shaping modern marketing while equipping themselves with actionable strategies to thrive in this dynamic environment. By delving into topics ranging from digital marketing and sustainability initiatives to data analytics and emerging technologies, Marketing Innovation Strategies and Consumer Behavior equips readers with the tools they need to survive and thrive in the modern marketplace. Its emphasis on real-world case studies ensures practical relevance, while its theoretical underpinnings offer a solid foundation for academic inquiry. This book is an indispensable resource for scholars seeking to deepen their understanding of marketing innovation, providing actionable insights and strategic frameworks to navigate the complexities of the digital age with confidence and agility.
Author: Amit Kumar Tyagi
Publisher: John Wiley & Sons
ISBN: 1394303572
Category : Computers
Languages : en
Pages : 628
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Book Description
An essential book on the applications of AI and digital twin technology in the smart manufacturing sector. In the rapidly evolving landscape of modern manufacturing, the integration of cutting-edge technologies has become imperative for businesses to remain competitive and adaptive. Among these technologies, Artificial Intelligence (AI) stands out as a transformative force, revolutionizing traditional manufacturing processes and making the way for the era of smart manufacturing. At the heart of this technological revolution lies the concept of the Digital Twin—an innovative approach that bridges the physical and digital realms of manufacturing. By creating a virtual representation of physical assets, processes, and systems, organizations can gain unprecedented insights, optimize operations, and enhance decision-making capabilities. This timely book explores the convergence of AI and Digital Twin technologies to empower smart manufacturing initiatives. Through a comprehensive examination of principles, methodologies, and practical applications, it explains the transformative potential of AI-enabled Digital Twins across various facets of the manufacturing lifecycle. From design and prototyping to production and maintenance, AI-enabled Digital Twins offer multifaceted advantages that redefine traditional paradigms. By leveraging AI algorithms for data analysis, predictive modeling, and autonomous optimization, manufacturers can achieve unparalleled levels of efficiency, quality, and agility. This book explains how AI enhances the capabilities of Digital Twins by creating a powerful tool that can optimize production processes, improve product quality, and streamline operations. Note that the Digital Twin in this context is a virtual representation of a physical manufacturing system, including machines, processes, and products. It continuously collects real-time data from sensors and other sources, allowing it to mirror the physical system’s behavior and performance. What sets this Digital Twin apart is the incorporation of AI algorithms and machine learning techniques that enable it to analyze and predict outcomes, recommend improvements, and autonomously make adjustments to enhance manufacturing efficiency. This book outlines essential elements, like real-time monitoring of machines, predictive analytics of machines and data, optimization of the resources, quality control of the product, resource management, decision support (timely or quickly accurate decisions). Moreover, this book elucidates the symbiotic relationship between AI and Digital Twins, highlighting how AI augments the capabilities of Digital Twins by infusing them with intelligence, adaptability, and autonomy. Hence, this book promises to enhance competitiveness, reduce operational costs, and facilitate innovation in the manufacturing industry. By harnessing AI’s capabilities in conjunction with Digital Twins, manufacturers can achieve a more agile and responsive production environment, ultimately driving the evolution of smart factories and Industry 4.0/5.0. Audience This book has a wide audience in computer science, artificial intelligence, and manufacturing engineering, as well as engineers in a variety of industrial manufacturing industries. It will also appeal to economists and policymakers working on the circular economy, clean tech investors, industrial decision-makers, and environmental professionals.
Author: Amit Kumar Tyagi
Publisher: John Wiley & Sons
ISBN: 139425833X
Category : Technology & Engineering
Languages : en
Pages : 470
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Book Description
A comprehensive reference on 6G wireless technologies, covering applications, hardware, security and privacy concerns, existing challenges, analytics methods, and much more 6G-Enabled Technologies for Next Generation delivers a thorough overview of the emerging sixth generation of wireless technology, presenting critical challenges of implementing 6G technologies including spectrum allocation, energy efficiency, security, interoperability, and more. Explaining ways we can use technologies to ensure a sustainable environment through renewable energy and a resilient industry, this book covers the applications and use cases such as smart grid, IoT, smart manufacturing, addressing security and privacy issues with privacy-preserving techniques and authentication control mechanisms. This book discusses the analytical methods used to study the performance of 6G technologies, covering simulation techniques, performance metrics, and predictive modeling. Introducing the core principles of 6G technology, including the advantages and disadvantages of the technology and how wireless communications have evolved, energy-efficient hardware and the different types of green communication technologies is explained. Many case studies are included in this book with a detailed explanation. Written by a team of experienced researchers, this book discusses: Terahertz (ThZ) communication, massive MIMO and beamforming, quantum communication, bandwidth management, and ultra-dense networks and small cell deployments Smart cities, telemedicine, and autonomous vehicles and schemes for waveform design, modulation, error correction, and advanced coding and modulation Sensor networks, edge computing and mobile cloud computing, and spatial, quantum, and dew computing Quantum-safe encryption, privacy-preserving technologies and techniques, threats and vulnerabilities, and authentication and access control mechanisms Network slicing and service differentiation, multi-connectivity and heterogeneous networks, and wireless power transfer 6G-Enabled Technologies for Next Generation is a comprehensive, up-to-date reference for students, academics, and researchers, along with professionals in the telecommunications field.
Author: Demir, Mahmut
Publisher: IGI Global
ISBN:
Category : Business & Economics
Languages : en
Pages : 333
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Book Description
The pressing challenges businesses face are rising, including the ethical considerations associated with artificial intelligence (AI) in the service industry. Revolutionizing the Service Industry with OpenAI Models is a book rooted in real-world examples and expert insights, which provides practical solutions by implementing the latest technology and explores the impact of AI-powered conversational agents on the service sector. The book commences with an enlightening introduction that underscores the transformative power of ChatGPT and OpenAI models, setting the stage for a deep dive into their role in reshaping the service industry. Through a systematic examination of current challenges and opportunities, the text unveils the innovations brought about by ChatGPT in customer service, revealing its potential to enhance response times, handle complex inquiries, and deliver personalized experiences on an unprecedented scale. Delving into designing conversational user interfaces, addressing language barriers, and deploying AI in sensitive sectors like healthcare, the book guides readers through responsible and effective implementation. It balances the exploration of AI-driven automation with understanding the importance of maintaining a human touch in service interactions. This book is ideal for business owners, managers, and decision-makers seeking to leverage AI-powered conversational agents for strategic advantage. Simultaneously, AI enthusiasts, researchers, and developers will find invaluable insights into the current issues, best practices, and future trends in AI-driven customer interactions.
Author: Revathy, G.
Publisher: IGI Global
ISBN:
Category : Computers
Languages : en
Pages : 393
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Book Description
The interaction of various service models, including edge computing and cloud computing, are quickly changing to better support microservices. This intricate weave of technology and information sharing is necessary to build systems that run faster and more efficiently. The interplay between these computing methods and microservices is emerging as the field of Osmotic Computing. Experts can now embark on an intellectual journey into data-driven exploration and ingenuity with the guidance of the book, Advanced Applications in Osmotic Computing. As ethical considerations become rising concerns, the potential biases, privacy encumbrances, and equitable conundrums of osmotic computing are investigated. This book offers judicious strategies to navigate these quandaries conscientiously, adding a layer of responsibility to the discourse. Within these pages, the very fabric of understanding in IoT, Cloud, Edge, Fog, and Machine Learning is redefined, marking a pivotal shift in the paradigm of technological comprehension. This book is an epicenter for the latest evolutions in osmotic computing, unfurling unconventional methodologies that shape the trajectory of data-driven decision-making. Readers will plunge into the theoretical bedrock, simultaneously witnessing pragmatic applications that adeptly bridge the schism between the theoretical constructs and pragmatic realization. The intended audience is multifaceted, encompassing data scientists, machine learning engineers, researchers, academics, educators, students, industry practitioners, interdisciplinary experts, and technology and business leaders.
