Notes for Deep Learning Specialization Courses led by Andrew Ng.

A Comprehensive Survey of Forgetting in Deep Learning Beyond Continual Learning. TPAMI, 2024.

A new test set for ImageNet

[TPAMI2022 & NeurIPS2020] Official implementation of Self-Adaptive Training

Developer Version of the R package CAST: Caret Applications for Spatio-Temporal models

JAX implementation of deep RL agents with resets from the paper "The Primacy Bias in Deep Reinforcement Learning"

TensorFlow in Practice Specialization. Join our Deep Learning Adventures community 🎉 and become an expert in Deep Learning, TensorFlow, Computer Vision, Convolutional Neural Networks, Kaggle Challenges, Data Augmentation and Dropouts Transfer Learning, Multiclass Classifications and Overfitting and Natural Language Processing NLP as well as Time…

PyTorch code for FLD (Feature Likelihood Divergence), FID, KID, Precision, Recall, etc. using DINOv2, InceptionV3, CLIP, etc.

[ICLR 2021] "Robust Overfitting may be mitigated by properly learned smoothening" by Tianlong Chen*, Zhenyu Zhang*, Sijia Liu, Shiyu Chang, Zhangyang Wang

Machine Learning to predict share prices in the Oil & Gas Industry

ICCV 2023 accepted paper, GPFL: Simultaneously Learning Global and Personalized Feature Information for Personalized Federated Learning

Tuning GBMs (hyperparameter tuning) and impact on out-of-sample predictions

A study on the following problems: what the memorization problem is in meta-learning; why memorization problem happens; and how we can prevent it. (ICLR 2020)

Official Codebase of "A Closer Look at Weakly-Supervised Audio-Visual Source Localization" (NeurIPS 2022)

All exercises for the course Elements of AI - Building AI

spatial resampling for more robust cross validation in spatial studies

Machine-Learning-Regression

**Supervised-Learning** (with some Kaggle winning solutions and their reason of Model Selection for the given dataset).

Deep Learning Adventures. Join our Deep Learning Adventures community 🎉 and become an expert in Deep Learning, TensorFlow, Computer Vision, Convolutional Neural Networks, Kaggle Challenges, Data Augmentation and Dropouts Transfer Learning, Multiclass Classifications and Overfitting and Natural Language Processing NLP as well as Time Series Forec…

playing with Dwork's adaptive holdout and how to use it for a grid-search