Skip to content

Latest commit

Β 

History

History
40 lines (29 loc) Β· 1.73 KB

README.md

File metadata and controls

40 lines (29 loc) Β· 1.73 KB

EL-3019-Data-Sciences

EL 3019 Data Sciences is an academic course πŸ‘¨β€πŸŽ“

Goals of the unit :

The aim of this unit is to provide an overview of data science, using libraries and frameworks. We work on famous data from gapminder or kaggle.

Packages used :

Python

anaconda

plotly

pandas

scikit-learn


Learned knowledge :

  • Deal with missing data
    • How to detect them
    • Typology of missing data
    • How to overcome them
  • Different types of classifiers, such as KNN, SVM, ...
  • Linear regression
  • Bayesian methodes

Some Interesting Plots :

matrix_corr

Matrix of correlation

pairplot pairplot

plotly_knn plotly_knn