yandexdataschool/mlhep2019
MLHEP'19 slides and notebooks
| repo name | yandexdataschool/mlhep2019 |
| repo link | https://github.com/yandexdataschool/mlhep2019 |
| homepage | |
| language | Jupyter Notebook |
| size (curr.) | 295748 kB |
| stars (curr.) | 31 |
| created | 2019-06-21 |
| license | MIT License |
MLHEP2019
MLHEP'19 slides and notebooks
Seminars:
- Day 1:
- Figures of Merit, overfitting (MLE vs MAP vs AP)
- Figures of Merit, overfitting (MLE vs MAP vs AP)
- Day 2:
- Ensembles of models; bagging, boosting, random forest
- Clustering
- Ensembles of models; bagging, boosting, random forest
- Day 3:
- Computing gradient by hand. Pytorch
- Convolutional Neural Networks ;
- Model Zoo:
- Computing gradient by hand. Pytorch
- Day 4:
- Bayesian 2
- Bayesian 2
- Day 5
- Learning to Pivot:
- toy example 1:
- toy example 2:
- toy example 3:
- SUSY exercise:
- toy example 1:
- Language modeling
- Tracking
- Learning to Pivot:
- Day 6
- Introductory example 1 :
- Introductory example 2 :
- Practice :
- GANs 1
- GANs 2
- GANs 3
- Introductory example 1 :
- Day 8
- Black-Box:
- ABO:
- AVO:
- ABO:
- NN optimisation
- 1-scikit-search:
- 2-skorch:
- 3-bayesian_optimization:
- 4-skorch_comet:
- 5-skorch_skopt_comet:
- 1-scikit-search:
- Independence of NN classifier from a continuous parameter:
- Black-Box:
