Attention (*Source: https://jasperwalshe.com/perspective-and-performance/) 1. Main ideas Convolutional neural networks (CNN) only focus...

1. Introduce Bayesian parameter estimation (Maximum-A-posterior) 2. An example 2.1. The pre-observation 2.2. The post-observation...

(*Source: Stefan Conrady - Bayesian Network Presentation)​ 1. Human and machine (*Source: Stefan Conrady - Bayesian Network...

I took part in Hackathon Techfest Munich at TU Munich in September, 2017. This was the first time I joined Hackathon. It was really...

Chapter 5 is very complicated to understand. That is why I publish this blog to summarize the knowledge in the Chapter 5. Basically, we...

1. Maximum-Likelihood estimate (MLE) Equation (1) (*Source: Richard O.Duda et al. Pattern Recognition) Equation (2) Equation (3) 2. MLE...

Equation (1) 1. Independent features with the same (common) covariance (*Source: Tso B. and Mather P. Classification Methods for Remotely...

(*Source: Richard O.Duda et al. Pattern Recognition) 1. Bayes decision rule 1.1. Risk function 1.1.1. Simple cost function (*Source:...

1. Normal distribution (*Source: https://en.wikipedia.org/wiki/Normal_distribution) 2. Multivariate normal densities​ (*Source:...

1. Discrete - Continuous random variable 1.1. Discrete random variable 1.2. Continuous random variable 2. Statistical independence 2.1....

There are three functions that facilitate functional programming: map, filter and reduce. To explain three functions, I will tell you...

1. Parallel strategies In the age of internet, computers need to process big data and the problem here is reduce running time. To reduce...