"Problem Solving in Data Structures & Algorithms" is a series of books about the usage of Data Structures and Algorithms in computer programming. The book is easy to follow and is written for interview preparation point of view. In various...
We show how to use "complementary priors" to eliminate the explaining-away effects that make inference difficult in densely connected belief nets that have many hidden layers. Using complementary priors, we derive a fast, greedy algorithm that can...
This book attempts to simplify and present the concepts of deep learning in a very comprehensive manner, with suitable, full-fledged examples of neural network architectures, such as Recurrent Neural Networks (RNNs) and Sequence to Sequence...