Entries by Yasuto Tamura

Illustrative introductions on dimension reduction

“What is your image on dimensions?” ….That might be a cheesy question to ask to reader of Data Science Blog, but most people, with no scientific background, would answer “One dimension is a line, and two dimension is a plain, and we live in three-dimensional world.” After that if you ask “How about the fourth […]

Spiky cubes, Pac-Man walking, empty M&M’s chocolate: curse of dimensionality

“Curse of dimensionality” means the difficulties of machine learning which arise when the dimension of data is higher. In short if the data have too many features like “weight,” “height,” “width,” “strength,” “temperature”…. that can undermine the performances of machine learning. The fact might be contrary to your image which you get from the terms […]

Understanding LSTM forward propagation in two ways

*This article is only for the sake of understanding the equations in the second page of the paper named “LSTM: A Search Space Odyssey”. If you have no trouble understanding the equations of LSTM forward propagation, I recommend you to skip this article and go the the next article. 1. Preface I  heard that in […]

A brief history of neural nets: everything you should know before learning LSTM

This series is not a college course or something on deep learning with strict deadlines for assignments, so let’s take a detour from practical stuff and take a brief look at the history of neural networks. The history of neural networks is also a big topic, which could be so long that I had to […]

Simple RNN: the first foothold for understanding LSTM

*In this article “Densely Connected Layers” is written as “DCL,” and “Convolutional Neural Network” as “CNN.” In the last article, I mentioned “When it comes to the structure of RNN, many study materials try to avoid showing that RNNs are also connections of neurons, as well as DCL or CNN.” Even if you manage to […]

Prerequisites for understanding RNN at a more mathematical level

Writing the A gentle introduction to the tiresome part of understanding RNN Article Series on recurrent neural network (RNN) is nothing like a creative or ingenious idea. It is quite an ordinary topic. But still I am going to write my own new article on this ordinary topic because I have been frustrated by lack of […]

A gentle introduction to the tiresome part of understanding RNN

Just as a normal conversation in a random pub or bar in Berlin, people often ask me “Which language do you use?” I always answer “LaTeX and PowerPoint.” I have been doing an internship at DATANOMIQ and trying to make straightforward but precise study materials on deep learning. I myself started learning machine learning in […]