Data-science

category-image

Statistics

category-image

Math

category-image

Python

category-image

Machine-learning

category-image

Definitions

category-image

Introduction to PAC Learning

What is “learning” and do we have a formal model for it? I’ve decided to dive into the theoretical underpinnings of machine-learning, so here’s a quick introduction to...

Machine-learning

Understanding p-values

Hypothesis testing and p-values are often misused and misunderstood. In this article, I explain what a p-value is, and how to use it.

Statistics

Polynomial basis expansion

Polynomial basis expansion, also called polynomial features augmentation, is part of the machine-learning preprocessing. It consists in adding powers of the input’s components to the input vector.

Machine-learning

The MSE loss

The mean squared error loss quantifies the error between a target variable and an estimate for its value.

Definitions

Train error and test error

The train error is the error commited by a machine-learning model on the dataset it was trained on. The test error is the error commited on another dataset...

Definitions

What is an hyperparameter?

An hyperparameter is a parameter of the machine-learning algorithm. While the parameters are learned by the machine-learning algorithm, an hyperparameter dictates how the algorithm learns.

Definitions

Scraping with Python3 and Scrapy

Scrapy is one of the most popular Python framework for large scale web scraping. It gives you all the tools you need to efficiently extract data from websites,...

Python

A Bayesian Perspective

Probability is not a property of an event or state; there is no such thing as the probability that the coin lands showing head. Probability expresses a strength...

Statistics