## Category: Machine Learning

Updated on November 8, 2017

## Your first CNN made easy with Docker and Tensorflow

Deep learning is the "new" trend, but more than a trend, related tools start to be quite mature. Convolutional neural networks (CNN) are particularly interesting and are a great source of research in visual recognition. With the help of Docker, …

Updated on October 15, 2016

## Generalized linear regression with Python and scikit-learn library

One of the most used tools in machine learning, statistics and applied mathematics in general is the regression tool. I say the regression, but there are lots of regression models and the one I will try to cover here is …

Updated on October 6, 2016

## Theano demo with Docker help

### What is Theano ?

From the Theano website:

Theano is a Python library that allows you to define, optimize, and evaluate mathematical expressions involving multi-dimensional arrays efficiently.

This is a demo of the library Theano commonly used …

Updated on October 31, 2015

## Gradient Descent Optimization

In many machine learning algorithm, the goal is to find a function or parameters that allows us to approximate or modelize unknown observable data. Those data could come from device measurement, web crawling, empirical observations etc. Generally speaking we have …

Updated on October 18, 2015

## k-means

For a first article, we'll see an implementation in Matlab of the so-called k-means clustering algorithm. K-means algorithm is a very simple and intuitive unsupervised learning algorithm. Indeed, with supervised algorithms, the input samples under which the training is performed …

Updated on October 18, 2015

## 2-D logistic regression

We have previously presented a proposed implementation for the k-means algorithm on computed samples. We saw that the result performed quite well clustering our samples. The next step now is to evaluate the probablility that a new sample belongs to …