The motivation behind writing this blog is to help those struggling in understanding the mathematics behind some machine learning algorithms and statistical concepts as a student like me.
What is more, this is also a good way to review as well as explain things to everyone as a means to push myself to understand the concepts better.
Latest Posts
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Bayesian Linear Regression
1 Introduction
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Gaussian Mixture Model with EM algorithm
Motivation
When it comes to clustering, there are many well-known unsupervised algorithms that could categorize the given data into many sensible groups, namely, K-mean & Hirarchical clustering algorithms. Yet,...
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Maximum Likelihood Estimation
Introduction
The goal of this topic is to introduce what does Maximum Likelihood Estimation (MLE) in statistics mean and the application of this method as well as the merits...
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Gaussian Processes
Introduction
In supervised learning approach, choosing a parametric model (e.g. linear reg, logistic reg and so on) is the most preferable way to do the predictive analysis, since the...
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