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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 ...
Slice Sampling
An implementation example of Slice Sampling for a special case: unimodal distribution with known inverse PDF
Rejection Sampling
Rejection is always painful, but it's for the greater good! You can sample from a complicated distribution by rejecting samples!
Metropolis-Hastings
An implementation example of Metropolis-Hastings algorithm in Python.
Gibbs Sampling
Example of Gibbs Sampling implementation in Python to sample from a Bivariate Gaussian.