Scikit-learn for Machine Learning

📄️ Data Loading

How to use Scikit-Learn's built-in datasets, fetchers, and external loaders to prepare data for modeling.

Transforming raw text into numerical features using Bag of Words, TF-IDF, and Scikit-Learn's feature extraction tools.

Transforming raw data into model-ready features using Scikit-Learn's preprocessing and imputation tools.

How to choose the right algorithm, split data correctly, and use Cross-Validation to ensure model reliability.

Optimizing model performance using GridSearchCV, RandomizedSearchCV, and Halving techniques.

How to use trained Scikit-Learn estimators to generate point predictions and probability estimates.