A multi-layer NN, able to process images and voice signals (2D), keep stability in rotations.
Continue reading “Deep Learning 05: Talk about Convolutional Neural Networks（CNN）”
Your life will be easier: when trying to use Principal Component Analysis.
Continue reading “Life will be easier: intro on PCA”
However, the post is mainly about Graph Partitioning.
Continue reading “Graph Partitioning on Gibbs Sampling”
About Decision Trees
* All samples will start from the root.
* At each node, one feature will split the samples.
Continue reading “Random Forest: intro and an example”
Logistic Regression is very popular in Machine Learning, used to give predictions on something. (It is not the exact probabilities, but general values. )
Continue reading “Logistic Regression: a quick introduction”
This post contains very basic knowledge of few sampling methods. As I am going to implement a java version of Gibbs Sampling, I went through some materials on the internet, and kept a learning journal here.
Will learn more about Gibbs Sampling in few days, and I will focus on how it involves with Graph Processing.
Continue reading “Sampling Methods”