#### Most popular articles this week

### Create your Machine Learning library from scratch with R ! (2/5)...

This is this second post of the "Create your Machine Learning library from scratch with R !" series. Today, we will see how you...

### Machine Learning Explained: supervised learning, unsupervised learning, and reinforcement learning

Machine learning is often split between three main types of learning: supervised learning, unsupervised learning, and reinforcement learning. Knowing the differences between these three types...

### Machine Learning Explained: Regularization

Welcome to this new post of Machine Learning Explained.After dealing with overfitting, today we will study a way to correct overfitting with regularization. Regularization adds...

#### R & R Shiny

### Explore your McDonalds Meal with Shiny and D3partitionR

Have you ever wondered what was in your MacDonalds menu? Or in your DoubleCheese Burger (well it's my favorite one)? A wonderful dataset was...

### The R Shiny packages you need for your web apps!

Shiny is an R Package to deploy web apps using an R backend. Let's face it, Shiny is awesome! It brings all the power...

### Three R Shiny tricks to make your Shiny app shines (3/3):...

In this tutorials sequence, we are going to see three tricks to do the following in a Shiny app:
Add Next and Previous buttons to...

#### Machine Learning Explained

### Machine Learning Explained: Vectorization and matrix operations

Today in Machine Learning Explained, we will tackle a central (yet under-looked) aspect of Machine Learning: vectorization. Let's say you want to compute the...

### Machine Learning Explained: Kmeans

Kmeans is one of the most popular and simple algorithm to discover underlying structures in your data. The goal of kmeans is simple, split your...

### Machine Learning Explained: Dimensionality Reduction

Dealing with a lot of dimensions can be painful for machine learning algorithms. High dimensionality will increase the computational complexity, increase the risk of...

#### Data science with python

### Machine Learning Explained: Vectorization and matrix operations

Today in Machine Learning Explained, we will tackle a central (yet under-looked) aspect of Machine Learning: vectorization. Let's say you want to compute the...

### Python Basics: Kmeans with Python

The K-means algorithm is one of the basic (yet effective) clustering algorithms. In this tutorial, we will have a quick look at what is...

### Python Basics: Logistic regression with Python

Logistic regression is one of the basics of data analysis and statistics. The goal of the regression is to predict an outcome, will I...

#### Data visualisation

### Explore your McDonalds Meal with Shiny and D3partitionR

Have you ever wondered what was in your MacDonalds menu? Or in your DoubleCheese Burger (well it's my favorite one)? A wonderful dataset was...

### Major update of D3partitionR: Interactive viz’ of nested data with R...

D3partitionR is an R package to visualize interactively nested and hierarchical data using D3.js and HTML widget. These last few weeks I've been working...