For TDS, so far 2017 has been the year of deep learning. We now hold a treasure trove of informative and speculative articles, but who’s got time to hunt through our archive to follow the Deep Learning trail?
We know our readers are busy professionals, so we’ve put together a selection of the top articles to help you follow the path from beginner to expert.
First steps
Deep Learning For Beginners by Shehzad Noor Taus Priyo (6 min read),
Linear algebra cheat sheet for deep learning by Brendan Fortuner (8 min read)
Basic Mathematics for Deep Learning by Tushar Gupta (7 min read)
Hardware for Deep Learning by Eugenio Culurciello (6 min read)
Climbing the hill
Neural Network Architectures by Eugenio Culurciello (14 min read),
Adding Uncertainty to Deep Learning by Motoki Wu (6 min read),
Pipelines, Mind Maps and Convolutional Neural Networks by Naoki Shibuya (11 min read),
Deep Learning: Back Propagation by Tushar Gupta (6 min read)
Standing atop the mountain
Opening the Neural Network Black Box – Perceptron by Meigarom Diego Fernandes (6 min read)
Building your own deep learning box by Brendan Fortuner (9 min read)
Generating text with deep learning by Dmitri Iourovitski (5 min read)
LSTM by Example using Tensorflow by Rowel Atienza (6 min read)
We also thank all the great new writers who joined us recently, Anastasia Anokhina, Lucian Lita, Aayush Chadha, Galina Dеgtyareva, Vivek Yadav, Cristian Ramirez, Ben Mann, Aneek Das, Prasanna Parasurama and Arnaldo Gunzi. There are more than 70 writers on our rolls, too many to list here, but we extend our thanks to every one of them. We invite you to take a look at their profiles and check out their work.