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​Introduction to Machine Learning with Python


This training is full. A new one will be organised in December.

More information coming soon.


Attendance:

Anyone willing to acquire basic Machine Learning skills


Objectives:

The objective of the training is to provide tools to build predictive models from a data set.

The focus of the training is on:

* Providing ready to use tools

* The Machine Learning process, from data preparation to model validation


Duration:

3 days: from 5th to 7th June 2019


Price:

Full price: 500 €

Reduced price (Paul Lambin Graduated students): 250 €


Training content:

1. Introduction to machine learning

2. Python for data sciences and machine learning

· Python 101 (data types, control structures)

· NumPy, Pandas and SkiKit-learn libraries

· Data manipulation with Python et Pandas

3. Supervised learning with SciKit-learn

· Regression vs. classification

· Data preparation and analysis

· Classic algorithms (regression, k-nearest neighbors, decision trees, Bayesian classifiers, kernel machine, neural network)

· Model validation and performance measure

· Model optimization

4. Unsupervised learning with Scikit-learn

· Data preparation and scaling

· Dimensionality reduction

· Rule inference and feature extraction

· Unsupervised clustering


Prerequisites:

* Some programming experience.

* Basic knowledge of descriptive statistics.

* This course will be taught in English.

A prior Python experience is not required.


Information : Cyrielle Thibaut



 
Formations
Type Court
Spécialisation