Category: AI/Machine Learning

Pytoch is a quite powerful, flexible and yet popular deep learning framework. The learning curve could be steep if you do not have much deep learning background. So what is…

debian 10 have nvidia GPU driver, cuda 9 etc, it is a good thing  for deep learning ( keras or pytorch). but  if let it running for some time (…

The normal use case is to discover interesting relations between variables in large databases, e.g: i(t) 1 ABDE 2 BCE 3 ABDE 4 ABCE 5 ABCDE 6 BCD the above…

K-means clustering is unsupervised machine learning algorithm. Wikipedia has a great demo as below on how it works: Demonstration of the standard algorithm 1. k initial “means” (in this case…

(1) Maximum the margin SVM is very easy to understand on the graph,, we just need to find the  a separate plane which maximum the margin. see the graph below: (2)…

The big picture is:  a quadratic programming problem can be reduced to be a linear programming problem. Here is how: (1) KTT conditions For any non-linear programming: max: f(x),  s.t: g(x)…

Why study the linear programming (LP) ? LP has a lot of use cases, one of them is the SVM ( support vector machine). The SVM ‘s Lagrangian dual can give…

In logistic regression, we just assume the probability of x to be classified as 1 is : P( y = 1 | x ) = 1 / ( 1 +…

Bayes theorem: where A and B are events and P(B) ≠ 0. P(A) and P(B) are the probabilities of observing A and B without regard to each other. P(A | B), a…

Decision tree works just like computer language if. In AI/ML world, the problem is usually like this: Given training set with features [( f1,f2 ….), ….] and known category/label [c1,…