Old Applied Data Analytics

COURSE  REGISTRATION: CLOSED !!   The course was in 2023
Course in english
  • Introduction to the capabilities and strengths of ML/DL with concrete examples of successful implementations; Big Data
  • How to implement a data analysis procedure:
    • Real data and simulated data
    • Real Data Acquisition and preparation
    • Formats of data and simulations: column data, images, time series;
    • Labelled and unlabelled datasets: supervised and unsupervised learning
    • Data quality, filtering, re-sampling
    • Missing data: interpolation, multiple imputation
    • Weighting input datasets
    • Data splitting
    • Feature-based supervised learning
    • Supervised Deep Learning
    • Regression and Classification
  • Feature-based supervised learning
    • Feature engineering;
    • Examples of algorithms: Boosted Decision Trees (BDTs) and Multilayer Perceptron (MLP)
  • Supervised Deep Learning
    • Image transformations
    • Network architecture
  • Data mining: Unsupervised learning for parameter space investigation through dimension reduction and visualization
  • Acceleration of simulations through Generative Adversarial Networks (GANs);
  • Analysis efficiency (ROC curve), definition of analysis cuts, extraction of searched signal from datasets, evaluation of the performance of the analysis
  • Final lecture on final considerations and suggestions
  • Two-hour session where each student presents her/his analysis challenges with 2 slides

November 2022

Email (contact pédagogique) : yvonne.becherini@apc.in2p3.fr

2 points


For doctoral school STEPUP :  please register through the usual google sheet  with code:  ED-SPU30-STE30

( In 2022 also  through Ametis : https://amethis.app.u-paris.fr/amethis-client/formation/gestion/formation/4852

For non UPC  students, you will need a certificate (« certificat de scolarité 2022-2023 ») proving that you belong to the doctoral school. Once you have it, please  sent  it to ced.formation.drive@u-paris.fr and sevrine.frimat@u-paris.fr to ask  for  your registration. )