Deep learning is a type of machine learning that empowers computers to learn from experience and understand the world in terms of a hierarchy of concepts. The book contains the mathematical and conceptual foundations of linear algebra, probability and information theory, numerical calculations and machine learning to the extent necessary to understand the material. Describes practical deep learning techniques, including deep feedforward networks, regularization, optimization algorithms, convolutional networks, sequence modeling, and more. Applications such as natural language processing, speech recognition, computer vision, online recommender systems, bioinformatics are considered. and video games.The publication is intended for undergraduate and graduate students, as well as experienced programmers who would like to use deep learning as part of their products or platforms.
Questions and answers
What is the book Deep Learning about in short?
The book 'Deep Learning' provides a comprehensive overview of deep learning, a subset of machine learning that enables computers to learn from experience. It covers essential mathematical and conceptual foundations, including linear algebra and probability, while also detailing practical techniques and applications in various fields such as natural language processing and computer vision.
What is the main idea of the book Deep Learning?
The main idea of 'Deep Learning' is to equip readers with the knowledge and skills necessary to understand and apply deep learning techniques effectively. It emphasizes the hierarchical nature of concepts in machine learning and provides insights into various algorithms and models that can be utilized in real-world applications, making it a vital resource for both students and professionals.
Who should definitely read the book Deep Learning?
This book is ideal for undergraduate and graduate students in computer science and related fields, as well as experienced programmers looking to integrate deep learning into their projects. It serves as a valuable resource for anyone interested in advancing their understanding of machine learning and its applications in technology and research.
What books is the book Deep Learning similar to?
Books similar to 'Deep Learning' include 'Pattern Recognition and Machine Learning' by Christopher Bishop, which also delves into machine learning concepts, and 'Deep Reinforcement Learning Hands-On' by Maxim Lapan, focusing on practical applications. These works complement the foundational knowledge provided in 'Deep Learning' and expand on specific areas within the field.
- Name of the Author
- Гудфеллоу Ян, Бенджио Иошуа, Курвилль Аарон
- Language
- Russian
- Age
- 12
- ISBN
- 978-5-97060-618-6
- Release date
- 2017
Read an excerpt
06/09/2025
Хорошая книга, но не без недостатков
Книга "Глубокое обучение" действительно содержит много ценной информации и охватывает широкий спектр тем, связанных с машинным обучением. Однако у меня остались некоторые сомнения относительно структуры изложения. Некоторые главы кажутся перегруженными техническими деталями, что может затруднить понимание для читателей, не обладающих глубокими знаниями в математике. В то же время, автор делает акцент на практическом применении теории, что, безусловно, является плюсом. Я был особенно впечатлён разделами о биоинформатике и рекомендательных системах. Однако, если вы ищете более лёгкое чтение, возможно, стоит рассмотреть другие источники. В целом, книга полезна, но требует времени и усилий для полного понимания.