Machine Learning by Andrew Ng_8 K-Means and PCA

Previous discussion is all about supervised learning, meaning there is a labeled or known output data pairs (x, y) for the algorithm to be trained. However, in real world, there are circumstances when intellectual creatures like human beings who can tell patterns without known data or first time. This is realized by another kind of … Continue reading Machine Learning by Andrew Ng_8 K-Means and PCA

Machine Learning by Andrew Ng_7 Support Vector Machine(SVM)

Another type of ML worth learning is SVM - support vector machine. The math behind is similar or derived from logistic regression with some mathematical substitution to get below: To be more concrete, it's main purpose is to achieve higher margin in terms of vector distance between data points and decision boundary Next, Kernel is … Continue reading Machine Learning by Andrew Ng_7 Support Vector Machine(SVM)

Machine Learning by Andrew Ng_5 Neuron Network

The hot word "neuron network" is part of machine learning. It follows the same math logic described before except in a more convoluted manners. In essence, the neuron unit can be regarded as one regression unit: Convolution occurs in the sense that there is hidden layer composed of multiple neurons to take into features from … Continue reading Machine Learning by Andrew Ng_5 Neuron Network

Machine Learning by Andrew Ng_4 Logistic Regression

The previous discussion is meant to solve predicting problem that is on continuous values. What if the value you try to predict is discretionary such as category A, B, or even just binary, positive or negative, yes or no etc. These are classification problems and the tool is not linear, or multivariate or polynomial regression … Continue reading Machine Learning by Andrew Ng_4 Logistic Regression

Multivariable Calculus_4 Integral of Vector Field and Multiple Integrals

It all starts from the leap jump accomplished by calculus in the attempt to calculate irregular shape. It does't take super smartness to go about by dividing the shape into infinitesimal small pieces, then sum up. But the sum-up is at most an approximation, not a finite, accurate value, what makes it accurate? That leap … Continue reading Multivariable Calculus_4 Integral of Vector Field and Multiple Integrals