GeezerVison is showing freecomputerbooks.com — Deep Learning Tutorials - Free Computer, Programming, Mathematics, Technical Books, Lecture Notes and Tutorials
Processing ......
Deep Learning Tutorials
- Title: Deep Learning Tutorials
- Author(s) LISA Lab
- Publisher: University of Montreal
- Hardcover/Paperback: 409 pages
- eBook: HTML and PDF
- Language: English
- ISBN-10: N/A
- ISBN-13: N/A
- Share This:
|
|
|
Book Description
Deep Learning is a new area of Machine Learning research, which has been introduced with the objective of moving Machine Learning closer to one of its original goals: Artificial Intelligence.
The tutorials presented here will introduce you to some of the most important deep learning algorithms and will also show you how to run them using Theano. Theano is a python library that makes writing deep learning models easy, and gives the option of training them on a GPU.
About the Authors
Reviews, Ratings, and Recommendations:
Related Book Categories:
Read and Download Links:
Similar Books:
-
Understanding Deep Learning (Simon J.D. Prince)
An authoritative, accessible, and up-to-date treatment of deep learning that strikes a pragmatic middle ground between theory and practice. Only the most important ideas to provide a high density of critical information in an intuitive and digestible form.
-
Manifold Learning: Model Reduction in Engineering
The aim is to provide tools for a better understanding and implement reduced order models by using: physics-based models, synthetic data forecast by these models, experimental data and deep learning algorithms.
-
-
The Little Book of Deep Learning (François Fleuret)
This book is a short introduction to deep learning for readers with a STEM background, originally designed to be read on a phone screen, is limited to the background necessary to understand a few important models.
-
-
Gradient Expectations: Structure of Predictive Neural Networks
An insightful investigation into the mechanisms underlying the predictive functions of neural networks - and their ability to chart a new path for AI. Delve into the known neural architecture of the mammalian brain to illuminate the structure of predictive networks.
-
-
Deep Learning (Ian Goodfellow, et al)
Written by three experts, this is the only comprehensive book on the subject. It offers mathematical and conceptual background, covering relevant concepts in linear algebra, probability theory and information theory, numerical computation, and machine learning.
-
Neural Networks and Deep Learning (Michael Nielsen)
Neural networks and deep learning currently provide the best solutions to many problems in image recognition, speech recognition, and natural language processing. This book will teach you the core concepts behind neural networks and deep learning.
Book Categories
Other Categories
Resources and Links