Lifelong Machine Learning, Second Edition, Sun, Zhiyuan Leno da Silva, Bing
Автор: Trevor Hastie; Robert Tibshirani; Jerome Friedman Название: The Elements of Statistical Learning ISBN: 0387848576 ISBN-13(EAN): 9780387848570 Издательство: Springer Рейтинг: Цена: 10480.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This major new edition features many topics not covered in the original, including graphical models, random forests, and ensemble methods. As before, it covers the conceptual framework for statistical data in our rapidly expanding computerized world.
Автор: Christopher M. Bishop Название: Pattern Recognition and Machine Learning ISBN: 1493938436 ISBN-13(EAN): 9781493938438 Издательство: Springer Рейтинг: Цена: 10480.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Familiarity with multivariate calculus and basic linear algebra is required, and some experience in the use of probabilities would be helpful though not essential as the book includes a self-contained introduction to basic probability theory.
Автор: Marc Peter Deisenroth, A. Aldo Faisal, Cheng Soon Ong Название: Mathematics for Machine Learning ISBN: 110845514X ISBN-13(EAN): 9781108455145 Издательство: Cambridge Academ Рейтинг: Цена: 6334.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This self-contained textbook introduces all the relevant mathematical concepts needed to understand and use machine learning methods, with a minimum of prerequisites. Topics include linear algebra, analytic geometry, matrix decompositions, vector calculus, optimization, probability and statistics.
Автор: Goodfellow Ian, Bengio Yoshua, Courville Aaron Название: Deep Learning ISBN: 0262035618 ISBN-13(EAN): 9780262035613 Издательство: MIT Press Рейтинг: Цена: 13543.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:
An introduction to a broad range of topics in deep learning, covering mathematical and conceptual background, deep learning techniques used in industry, and research perspectives.
"Written by three experts in the field, Deep Learning is the only comprehensive book on the subject." -- Elon Musk, cochair of OpenAI; cofounder and CEO of Tesla and SpaceX
Deep learning is a form of machine learning that enables computers to learn from experience and understand the world in terms of a hierarchy of concepts. Because the computer gathers knowledge from experience, there is no need for a human computer operator to formally specify all the knowledge that the computer needs. The hierarchy of concepts allows the computer to learn complicated concepts by building them out of simpler ones; a graph of these hierarchies would be many layers deep. This book introduces a broad range of topics in deep learning.
The text offers mathematical and conceptual background, covering relevant concepts in linear algebra, probability theory and information theory, numerical computation, and machine learning. It describes deep learning techniques used by practitioners in industry, including deep feedforward networks, regularization, optimization algorithms, convolutional networks, sequence modeling, and practical methodology; and it surveys such applications as natural language processing, speech recognition, computer vision, online recommendation systems, bioinformatics, and videogames. Finally, the book offers research perspectives, covering such theoretical topics as linear factor models, autoencoders, representation learning, structured probabilistic models, Monte Carlo methods, the partition function, approximate inference, and deep generative models.
Deep Learning can be used by undergraduate or graduate students planning careers in either industry or research, and by software engineers who want to begin using deep learning in their products or platforms. A website offers supplementary material for both readers and instructors.
Автор: Hackeling Gavin Название: Mastering Machine Learning with scikit-learn, Second Edition ISBN: 1788299876 ISBN-13(EAN): 9781788299879 Издательство: Неизвестно Рейтинг: Цена: 9010.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
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.
The updated edition of this practical book uses concrete examples, minimal theory, and three production-ready Python frameworks--scikit-learn, Keras, and TensorFlow--to help 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.
Описание: This book provides an insight into ways of inculcating the need for applying mobile edge data analytics in bioinformatics and medicine. The contributors also include information on microarray data analysis, sequence analysis, genomics based analytics, disease network analysis, and techniques for big data Analytics and health information technology.
Описание: This book constitutes selected and extended papers from the Second International Workshop on Deployable Machine Learning for Security Defense, MLHat 2021, held in August 2021. The papers are organized in topical sections on machine learning for security, and malware attack and defense.
Описание: This updated second edition of Mastering Azure Machine Learning is a critically timed book. It builds upon simple and advanced NLP techniques, ML models such as boosted trees, deep neural network architectures, and more to help you leverage the power of Azure Machine Learning Services.
Автор: Neapolitan, Richard E. Jiang, Xia Название: Artificial intelligence ISBN: 0367571641 ISBN-13(EAN): 9780367571641 Издательство: Taylor&Francis Рейтинг: Цена: 6430.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: The first edition of this popular textbook, Contemporary Artificial Intelligence, provided an accessible and student friendly introduction to AI. This fully revised and expanded update retains the same accessibility and problem-solving approach, while providing new material and methods, including neural networks and deep learning.
Автор: Sharma Aditya, Shrimali Vishwesh Ravi, Beyeler Michael Название: Machine Learning for OpenCV 4- Second Edition ISBN: 1789536308 ISBN-13(EAN): 9781789536300 Издательство: Неизвестно Рейтинг: Цена: 9010.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Machine Learning for OpenCV 4, Second Edition will help the readers to implement and train machine learning algorithms with OpenCV 4 and scikit-learn in Python. By the end of this book, you will be able to build intelligent applications with OpenCV 4 using various optimization techniques for your machine learning algorithms.
Автор: Jansen Stefan Название: Machine Learning for Algorithmic Trading - Second Edition ISBN: 1839217715 ISBN-13(EAN): 9781839217715 Издательство: Неизвестно Рейтинг: Цена: 12665.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This thoroughly revised and expanded second edition demonstrates on over 800 pages how machine learning can add value to algorithmic trading in a practical yet comprehensive way. It has four parts that cover how to work with a diverse set of market, fundamental, and alternative data sources, design ML solutions for real-world trading ...
ООО "Логосфера " Тел:+7(495) 980-12-10 www.logobook.ru
