ai24-7 / kaggle-notebooks Goto Github PK

You can run these notebooks on cloud platforms like Kaggle Colab or your local machine. Note that most chapters require a GPU even TPU sometimes to run in a reasonable amount of time, so we recommend one of the cloud platforms as they come pre-installed with CUDA.

To run these notebooks on a cloud platform, just click on one of the badges (Colab or Kaggle) in the table below. The code will be reproduced from Github directly onto the choosen platform (you may have to add the necessary data before running it). Alternatively, we also provide links to the fully working original notebook on Kaggle that you can copy and immediately run.

no	Chapter	Notebook	Colab	Kaggle
05	Competition Tasks and Metrics	meta_kaggle
06	Designing Good Validation	adversarial-validation-example
07	Modeling for Tabular Competitions	interesting-eda-tsne-umap
		meta-features-and-target-encoding
		really-not-missing-at-random
		tutorial-feature-selection-with-boruta-shap
08	Hyperparameter Optimization	basic-optimization-practices
		hacking-bayesian-optimization-for-dnns
		hacking-bayesian-optimization
		kerastuner-for-imdb
		optuna-bayesian-optimization
		scikit-optimize-for-lightgbm
		tutorial-bayesian-optimization-with-lightgbm
09	Ensembling with Blending and Stacking Solutions	ensembling
10	Modeling for Computer Vision	augmentations-examples
		images-classification
		prepare-annotations
		segmentation-inference
		segmentation
		object-detection-yolov5
11	Modeling for NLP	nlp-augmentations4
		nlp-augmentation1
		qanswering
		sentiment-extraction
12	Simulation and Optimization Competitions	connectx
		mab-santa
		rps-notebook1

1. Introducing Kaggle and Other Data Science Competitions
2. Organizing Data with Datasets
3. Working and Learning with Kaggle Notebooks
4. Leveraging Discussion Forums

5. Competition Tasks and Metrics
6. Designing Good Validation
7. Modeling for Tabular Competitions
8. Hyperparameter Optimization
9. Ensembling with Blending and Stacking Solutions
10. Modeling for Computer Vision
11. Modeling for NLP
12. Simulation and Optimization Competitions

13. Creating Your Portfolio of Projects and Ideas
14. Finding New Professional Opportunities