Back
Tags: #programming
-
How to Use Specific Image and Description when Sharing Jekyll Post to Facebook
Normally, random subset of pictures and the site's description will be picked when we shared our Jekyll blog post URL ...
-
Deriving LSTM Gradient for Backpropagation
Deriving neuralnet gradient is an absolutely great exercise to understand backpropagation and computational graph better. In this post we will ...
-
Convnet: Implementing Maxpool Layer with Numpy
Another important building block in convnet is the pooling layer. Nowadays, the most widely used is the max pool layer. ...
-
Convnet: Implementing Convolution Layer with Numpy
Convnet is dominating the world of computer vision right now. What make it special of course the convolution layer, hence ...
-
Implementing BatchNorm in Neural Net
BatchNorm is a relatively new technique for training neural net. It gaves us a lot of relaxation when initializing the ...
-
Implementing Dropout in Neural Net
Dropout is one simple way to regularize a neural net model. This is one of the recent advancements in Deep ...
-
Beyond SGD: Gradient Descent with Momentum and Adaptive Learning Rate
There are many attempts to improve Gradient Descent: some add momentum, some add adaptive learning rate. Let's see what's out ...
-
Implementing Minibatch Gradient Descent for Neural Networks
Let's use Python and Numpy to implement Minibatch Gradient Descent algorithm for a simple 3-layers Neural Networks.
-
Paralellizing Monte Carlo Simulation in Python
Monte Carlo simulation is all about quantity. It can take a long time to complete. Here's how to speed it ...
-
Scrapy as a Library in Long Running Process
Scrapy is a great web crawler framework, but it's tricky to make it runs as a library in a long-running ...