Machine learning is the science of getting computers to act without being explicitly programmed. Machine learning has given us self-driving cars.
“One learning algorithm” hypothesizes that human intelligence may be due to one learning algorithm. Unfortunately, we are not there yet. Machine Learning (ML) starts from many disciplines and there are a lot of concepts to learn. Sometimes these concepts are explained with too much abstraction or on the contrary, too little substance. In this ML article, we will study the fundamental like information theory, probability, distribution, Bayesian inference, PCA, Statistical Significance, etc … Having a solid understanding of the basic is important for ML.