advanced_ml_from_scratch

Implementation of machine learning algorithms from scratch

The following algorithms/use-cases are implemented to date:

Data Sources: Google

Name		Name	Last commit message	Last commit date
Latest commit History 11 Commits
data		data
mongoDB		mongoDB
README.md		README.md
alternating_least_squares.ipynb		alternating_least_squares.ipynb
anomaly_detection.ipynb		anomaly_detection.ipynb
cnn_blocks.ipynb		cnn_blocks.ipynb
contrastive_learning.ipynb		contrastive_learning.ipynb
decision_tree.ipynb		decision_tree.ipynb
denoising_autoencoder.ipynb		denoising_autoencoder.ipynb
entity_embeddings.ipynb		entity_embeddings.ipynb
expectation_minimization.ipynb		expectation_minimization.ipynb
factorization_machines.ipynb		factorization_machines.ipynb
fairness.ipynb		fairness.ipynb
learning_to_rank.ipynb		learning_to_rank.ipynb
multi_armed_bandits.ipynb		multi_armed_bandits.ipynb
multi_task_learning.ipynb		multi_task_learning.ipynb
named_entity_recognition.ipynb		named_entity_recognition.ipynb
object_detection_metrics.ipynb		object_detection_metrics.ipynb
opencv_transformations.ipynb		opencv_transformations.ipynb
semi_supervised_learning.ipynb		semi_supervised_learning.ipynb
sequential_modelling_LSTM.ipynb		sequential_modelling_LSTM.ipynb
sparsity.ipynb		sparsity.ipynb
statistical_tests.ipynb		statistical_tests.ipynb
thompson_sampling.ipynb		thompson_sampling.ipynb
time_series_ARIMA.ipynb		time_series_ARIMA.ipynb
tokenizers_BPE.ipynb		tokenizers_BPE.ipynb
understanding_AUC.ipynb		understanding_AUC.ipynb
unet_model.ipynb		unet_model.ipynb

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