- Logistic Regression, Overfitting & regularization
- Data Preprocessing (missing/categorical data)
- Data Preprocessing II - Partitioning a dataset / Feature scaling / Feature Selection / Regularization
- Data Preprocessing III - Dimensionality reduction vis Sequential feature selection / Assessing feature importance via random forests
- Data Compression via Dimensionality Reduction I - Principal component analysis (PCA)
- Data Compression via Dimensionality Reduction II - Linear Discriminant Analysis (LDA)
- Data Compression via Dimensionality Reduction III - Nonlinear mappings via kernel principal component (KPCA) analysis
- Natural Language Processing (NLP): Sentiment Analysis I (IMDb & bag-of-words)
- Natural Language Processing (NLP): Sentiment Analysis II (tokenization, stemming, and stop words)
- Natural Language Processing (NLP): Sentiment Analysis III (training & cross validation)
- Natural Language Processing (NLP): Sentiment Analysis IV (out-of-core)
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