Additional websites
The webpage of G. Saes with his lectures on GenAI
A full course on NLP on this website
Hugging face material on LLMs
Hugging face material on AI agents
Part II : Deep Learning
Introduction to NLP :
NLP1.pdf. Companion notebook : NLP1.ipynb
Introduction to Neural Networks :
Part I : Classical ML
Lecture 7
Course 7a : Random Controlled Trials
Course 7a : Course7a.pdf,
Notebook : Lecture7a.ipynb. Dataset : village.csv
RCT and ecometry : E. Duflo
Course 7b : Deal with Observational data
Course 7b : Course7b.pdf
Lecture 7b : Lecture7b.ipynb
Observational data : G. Imbens
Lab 7
Dataset : ihdp.csv
A recent judgement of the European court
Course 6 : Time Series Forecasting
Lecture 6a : Lecture6a.pdf, Lecture6a.ipynb
Datasets related to Lecture 6a : internet-traffic.csv, quebec.csv
Lecture 6b : Lecture6b.pdf, Lecture6b.ipynb
Datasets related to Lecture 6b : calendar.csv, sales_train_evaluation.csv, sell_prices.csv
Lecture 6c : Lecture6c.ipynb
Lab 6 : Lab6.pdf.
Dataset : PJME_hourly.csv
Course 5 : advanced supervised learning
Lecture 5 on conformal prediction : Lecture5.pdf
Notebooks : ComputerExample.ipynb, Lecture5.ipynb, QuantileRegression.ipynb and ConformalPrediction. ipynb
Datasets : diamonds.csv
Practical Session 5
Lab 5 : Lab5.pdf. Dataset : dataset.csv
Notebook of Lab5 : Lab5.ipynb
Course 4 : Basics on supervised learning
Overview of supervised learning : OverviewSupervised.pdf
Some websites related to Course 4
Two websites about regression : Vanilla linear regression and Ridge-vs-Lasso
Linear regression with sklearn : website. Dataset : bottle.csv. Notebook : VanillaLinearRegression.ipynb
A website on Logistic regression. Python implementation . Notebook : LogisticRegression.ipynb
More on decision trees. Two Python examples : classification trees and regression trees
Datasets : balance-scale.csv.
Notebook for classification trees: ClassificationTree.ipynb
Evaluation : ConfusionMatrix
Notebook for regression trees : RegressionTree.ipynb
Random Forest in Python : this website with the dataset PositionSalaries.csv
Notebook for Random Forest : RandomForest.ipynb
Evaluation in regression : oob-score , R2. More details here
More on feature importance with Random Forest : this website
Practical Session 4
Lab4 : Lab4.pdf
Notebook of Lab 4 : Lab4.ipynb
Course 3: Basics on clustering
Overview of unsupervised learning : Overview-Clustering.pdf
Lecture on clustering : Clustering.pdf. Notebook : Clustering. ipynb
The scikit-learn website
Lab on clustering : Lab.pdf
Dataset : Live.csv
Notebook : LabClustering.ipynb
Some websites about clustering
See Hierarchical Clustering and this Medium website for Hierachical Clustering
Course 2 : Basics on machine learning
Lecture 2 : OverviewML.pdf
Course 1 : Basics on Random Variables with Python
First lecture on Random Variables : CM_RandomVariables.pdf. Notebook of Lecture 1 : Lecture1.ipynb
Tutorial on Seaborn : Seaborn.ipynb. Iris dataset : iris.csv
Exploratory Data Analysis : EDA1.pdf. Data : Ames.csv. Notebook : EDA.ipynb