Course/Event Essentials
Event/Course Start
Event/Course End
Event/Course Format
Mixed
Live (synchronous)
Primary Event/Course URL
Training Content and Scope
Scientific Domain
Technical Domain
Level of Instruction
Intermediate
Sector of the Target Audience
Research and Academia
Industry
Public Sector
HPC Profile of Target Audience
Application Developers
Data Scientists
Language of Instruction
Other Information
Organiser
Supporting Project(s)
EuroCC2/CASTIEL2
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.