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Create your Machine Learning library from scratch with R ! (3/5) – KNN

May 23, 2018
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Create your Machine Learning library from scratch with R ! (3/5) – KNN

This is this second post of the “Create your Machine Learning library from scratch with R !” series. Today, we will see how you can implement K nearest neighbors (KNN) using only the linear algebra available in R. Previously, we managed to implement PCA and next time we will deal with SVM and decision trees. The post Create your...

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Create your Machine Learning library from scratch with R ! (2/5) – PCA

May 15, 2018
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Create your Machine Learning library from scratch with R ! (2/5) – PCA

This is this second post of the “Create your Machine Learning library from scratch with R !” series. Today, we will see how you can implement Principal components analysis (PCA) using only the linear algebra available in R. Previously, we managed to implement linear regression and logistic regression from scratch and next time we will The post Create your...

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Machine Learning Explained: Vectorization and matrix operations

May 7, 2018
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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 sum of the values of an array. The naive way to do so is to loop over the elements and to sequentially sum them. This naive way is slow and tends The post Machine Learning...

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Create your Machine Learning library from scratch with R ! (1/3)

January 30, 2018
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Create your Machine Learning library from scratch with R ! (1/3)

When dealing with Machine Learning problems in R, most of the time you rely on already existing libraries. This fastens the analysis process, but do you really understand what is behind the algorithms? Could you implement a logistic regression from scratch with R? The goal of this post is to create our own basic machine The post Create your...

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Machine Learning Explained: Kmeans

October 24, 2017
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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 data in k different groups represented by their mean. The mean of each group is assumed to be a good summary of each observation of this cluster. Kmeans Algorithm We assume The post Machine Learning...

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Explore your McDonalds Meal with Shiny and D3partitionR

October 2, 2017
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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 released a few months ago, it contains all the nutrition facts from McDonald’s items. You can find the dataset here. In addition to this, I released a new version of D3partitionR a few The post Explore your...

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Major update of D3partitionR: Interactive viz’ of nested data with R and D3.js

September 20, 2017
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Major update of D3partitionR: Interactive viz’ of nested data with R and D3.js

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 on a major D3partitionR update which is now available on GitHub. As soon as enough feedbacks are collected, the package will be on uploaded on the CRAN. Until then, you can The post Major update...

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