Differential calculus is an important tool in machine learning algorithms. Neural networks in particular, the gradient descent algorithm depends on […]
Author Archive | Adrian Tam
Visualizing the vanishing gradient problem
Deep learning was a recent invention. Partially, it is due to improved computation power that allows us to use more […]
Using CNN for financial time series prediction
Convolutional neural networks have their roots in image processing. It was first published in LeNet to recognize the MNIST handwritten […]
Face Recognition using Principal Component Analysis
Recent advance in machine learning has made face recognition not a difficult problem. But in the previous, researchers have made […]
Using Singular Value Decomposition to Build a Recommender System
Singular value decomposition is a very popular linear algebra technique to break down a matrix into the product of a […]
A Gentle Introduction to Vector Space Models
Vector space models are to consider the relationship between data that are represented by vectors. It is popular in information […]
Principal Component Analysis for Visualization
Principal component analysis (PCA) is an unsupervised machine learning technique. Perhaps the most popular use of principal component analysis is […]
Optimization for Machine Learning Crash Course
Optimization for Machine Learning Crash Course. Find function optima with Python in 7 days. All machine learning models involve optimization. […]
How to Learn Python for Machine Learning
Python has become a defacto lingua franca for machine learning. It is not a difficult language to learn, but if […]
Training-validation-test split and cross-validation done right
One crucial step in machine learning is the choice of model. A suitable model with suitable hyperparameter is the key […]