Answer» - Logistic regression, naive Bayes: Use for Classification.
- Generalized LINEAR regression, SURVIVAL regression: Perform Regression technique.
- Decision trees, random forests, and gradient-boosted trees
- Alternating least squares (ALS): For Recommendation
- K-means, Gaussian MIXTURES (GMMs): To performs Clustering
- Latent Dirichlet allocation (LDA): To perform modeling
- Sequential pattern mining: Frequent item sets, association rule mining.
- Featurization: feature extraction, transformation, dimensionality reduction, and selection
- Pipelines: tools for constructing, evaluating, and tuning ML Pipelines
- Persistence: SAVING and LOAD algorithms, models, and Pipelines
- Utilities: linear algebra, statistics, data handling, etc.
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