First approach to machine learning

Wandering through the field of study that gives computers the ability to learn without being explicitly programmed. Mainly based on Machine Learning course @ Coursera.

Articles in this series

1. Introduction to machine learning

What machine learning is about, types of learning and classification algorithms, introductory examples. written on March 12, 2016

2. Linear regression with one variable

Finding the best-fitting straight line through points of a data set. written on April 01, 2016

3. The gradient descent function

How to find the minimum of a function using an iterative algorithm. written on February 05, 2017

4. The gradient descent in action

It's time to put together the gradient descent with the cost function, in order to churn out the final algorithm for linear regression. written on February 18, 2017

5. Multivariate linear regression

How to upgrade a linear regression algorithm from one to many input variables. written on March 05, 2017

6. How to optimize the gradient descent algorithm

A collection of practical tips and tricks to improve the gradient descent process and make it easier to understand. written on April 01, 2017

7. Introduction to classification and logistic regression

Get your feet wet with another fundamental machine learning algorithm for binary classification. written on July 17, 2017

8. The cost function in logistic regression

Preparing the logistic regression algorithm for the actual implementation. written on October 29, 2017

9. The problem of overfitting in machine learning algorithms

Overfitting makes linear regression and logistic regression perform poorly. A technique called "regularization" aims to fix the problem for good. written on September 02, 2018