Elpis - Resource Allocation System

This is a two part workshop.
material: Python, Pandas, Numpy, Scikit Learn.
objective: You will be introduced to the large landscape of machine learning and neural network techniques. You will learn how to select, write, train and test an ML model using the machine learning library application programming interface (api). You will be able to match a machine learning technique to the problem that you will need to solve.
Introduction to machine learning with examples: getting preliminary experience with the use of Python's machine learning library, Scikit Learn, and understanding the different preprocessing steps before the implementation of the ML model.
Predictive analysis: regression.
Classification with SVM, decision trees and random forest.
Dimension redaction and feature selection: PCA, kernel PCA. Feature importance with random forest.
Non-supervised machine learning methods: Clustering with Kmeans and Hierarchical Clustering.
Guided solution of a mini-project.