Python for Machine learning

Course/Event Essentials

Event/Course Start
Event/Course End
Event/Course Format

Venue Information

Country: Belgium
Venue Details: Click here

Training Content and Scope

Scientific Domain
Level of Instruction
Sector of the Target Audience
Research and Academia
Public Sector
HPC Profile of Target Audience
Application Developers
Data Scientists
Language of Instruction

Other Information

Event/Course Description

Topics covered

Python is one of the dominant languages in the area of machine learning.

This training will provide an introduction to machine learning methodology as well as some machine learning algorithms. 

Subjects and Python modules that will be covered:

  • what is machine learning, and what is AI?
  • pipelines for data ingestion, training and testing: scikit-learn
  • examples of classic algorithms: scikit-learn
    • principal component analysis
    • Ridge regression
    • Naive Bayes classifier
    • k-means clustering
  • examples of (deep) neural networks: Keras
    • multi-layer perceptron for image classification
    • convolutional neural network for image classification
    • recurrent neural networks for sentiment analysis

Target audience

Experience in Python programming, visualization.