wikistat / High-Dimensional-Deep-Learning
Science des données Saison 4 : Apprentissage en grande dimension, Données fonctionnelles, Détection d'anomalies, Introduction au Deep Learning
☆39Updated 7 months ago
Related projects: ⓘ
- Science des Données Saison 3: Apprentissage Automatique / Statistique pour l'Intelligence Artificielle☆50Updated last year
- Science des Données Saison 2: Exploration statistique multidimensionnelle, ACP, AFC, AFD, Classification non supervisée☆41Updated 7 months ago
- Machine Learning Training for Data Science and AI ... Bootcamp in progress☆15Updated 11 months ago
- Python pour Statistique et Science des Données -- Syntaxe, Trafic de Données, Graphes, Programmation, Apprentissage☆30Updated 5 years ago
- Science des Données Saison 1: Description statistique, estimation, tests, régression linéaire simple, multiple. Modèle linéaire général.☆14Updated 5 years ago
- Python tutorial on machine learning with time series for DSSGx 2020☆23Updated 4 years ago
- TensorFlow Probability Tutorial☆36Updated 4 years ago
- A toolbox for fair and explainable machine learning☆52Updated 3 months ago
- Utilities to perform Uncertainty Quantification on Keras Models☆112Updated 6 months ago
- Machine Learning vs Statistical Methods for Time Series Forecasting: Size Matters☆38Updated 4 years ago
- Science des Données Saison 5: Technologies pour l'apprentissage automatique / statistique de données massives et l'Intelligence Artificie…☆44Updated last year
- Fair Statistical Learning Algorithms for Ethical Artificial Intelligence☆25Updated last year
- Workshop on Bayesian inference using PyMC☆26Updated 3 years ago
- ☆12Updated last year
- ☆14Updated last year
- causal inference in python, have been reading judea pearl's book of why☆16Updated 5 years ago
- Tensorflow implementation of deep quantile regression☆77Updated 2 years ago
- Material for ODSC Europe presentation -- Probabilistic Deep Learning in TensorFlow, the why and the how☆70Updated 4 years ago
- How to Interpret SHAP Analyses: A Non-Technical Guide☆42Updated 2 years ago
- Bayesian neural networks via MCMC: tutorial☆29Updated 5 months ago
- Materials for conference talks and workshops☆28Updated 8 months ago
- Course notes for graduate-level class on numerical methods for deep learning☆49Updated 3 years ago
- CinnaMon is a Python library which offers a number of tools to detect, explain, and correct data drift in a machine learning system☆75Updated last year
- This course is an overview of applied causal inference.☆29Updated last year
- Course material for 1RT700 Statistical Machine Learning☆58Updated 7 months ago
- Implementation for Stankevičiūtė et al. "Conformal time-series forecasting", NeurIPS 2021.☆65Updated last month
- ☆40Updated 5 years ago
- A python multi-variate time series prediction library working with sklearn☆90Updated 3 years ago
- An sklearn style implementation of the Relevance Vector Machine (RVM).☆23Updated 4 years ago
- Uncertainty Estimation Using Deep Neural Network and Gradient Boosting Methods☆23Updated 3 years ago