The Deep Learning textbook is a resource intended to help students and practitioners enter the field of machine learning in general and deep learning in particular.

Learning deep structured semantic models for web search using clickthrough data. In Proceedings of the 22nd ACM international conference on Conference on information & …

P art I I Deep Net w orks: Mo dern Practices 162 This part of the b o ok summarizes the state of mo dern deep learning as it is

CHAPTER 2. LINEAR ALGEBRA example, we might say “Let s ∈R b e the slop e of the line,” while defining a real-v alued scalar, or “Let n ∈N b e the num b er of units,” while defining a

Ian's presentation at the 2016 Re-Work Deep Learning Summit. Covers Google Brain research on optimization, including visualization of neural network cost functions, Net2Net, and batch …

Explanation of recurrent neural networks, their architecture, and applications in deep learning.

of machine learning tec hniques and b eing go o d at differen t kinds of math. In prac- tice, one can usually do muc h b etter with a correct application of a commonplace

Visible layer (input pixels) Figure 1.2: Illustration of a deep learning Figure model. It is difficult for a computer to understand the meaning of raw sensory input data, such as 1.2 this image …

• Chapter 16, Structured Probabilistic Models for Deep Learning: Deng Qingyu , Harry Braviner, Timoth y Cogan, Diego Marez, Anton V arfolom and Victor

A comprehensive textbook on machine learning and deep learning, covering theory, applications, and research.