Learning Notes 🍰🧁🍪🍺

Presentations

• PyTorch Image Classification Common Code Template
• PyTorch Transformer: Tokenizer, Text Classification and Question Answering
• LDA
• Model Interpretation: LIME and Shapley
• Kaggle Prostate Image Classification
• SQL Window Function Tutorial

Deep Learning

• Large_Language_Models.md
• LLM_and_prompt_engineering.md
• GAN_and_Diffusion_models.md
• Variational AutoEncoder.md
• more_on_Transformer.md
• more_on_RNN.md
• quantization_pruning_distillation.md
• PyTorch_basics_1.md
• PyTorch_basics_2.md
• nn.LossFunctions.md
• Graph_Neural_Network.md
• question_answering_indexing.pdf
• Gated_Recurrent_Unit.pdf
• deep_reinforcement_learning.pdf
• transposed_convolution_upsampling.pdf
• U-Net.md
• augmentation.md
• Inception_network.md
• prepare_numerical_data_for_NN.md

Traditional Machine Learning

(i) Thoughts

• credit_risk_feature_creation.md
• multiclass_classification_feature_selection.ipynb
• feature_stability_classification_models.md
• train_deploy_pipeline_matching.pdf
• sliding_window_cross_validation.md
• tabular_data_train_val_split.md
• simple_deployment.md
• structure_of_main_scripts.md
• AUC_interpretation.pdf
• high_accuracy_low_F1.md
• gap_between_train_and_test_performance_matters.md
• more_features_than_samples.md
• churn_model_misled_by_a_category_popular_in_the_past.md
• calculate_financial_benefit.md
• monitor_performance_and_treatment_effectiveness.md
• bi_encoder_cross_encoder.md

(ii) Learning

• more_on_XGB.md
• designing_machine_learning_systems.md
• area_under_precision_recall_curve.md
• Coursera_how_to_win_a_data_science_competition.pdf
• LDA.md
• recommender_systems.pdf
• recommender_system_vs_propensity_models.md
• GBDT+LR.md
• customize_loss_function.md
• evaluation_metrics.md
• sklearn_pipeline_and_transformer.md
• word_embedding_for_topic_modelling.md
• ML_fairness.md
• extrapolate_GBRT_for_time_series.md
• Sagemaker_templates
• uplift_model.md
• customer_lifetime_value.md

Statistics

• meaning_common_distributions.md
• Fourier_Transform_and_Melspectrogram.ipynb
• Singular_Value_Decomposition.ipynb
• AB_testing.md
• linear_regression_remedial_measures.md
• rule_of_three.md
• James_Stein_estimator_and_Steins_paradox.md
• rule_of_succession.md
• Good_Turing_frequency_estimation.md
• survival_analysis.md

Programming

• python_trick_collection_1.ipynb
• python_trick_collection_2.ipynb
• python_trick_collection_3.ipynb
• python_trick_collection_4.ipynb
• algorithms.md
• PySpark_notes.md
• git_and_shell_tricks.md

Small Learning

• small_learning.md