Tools

• pandas — data manipulation and analysis
• NumPy — numerical computing
• Matplotlib — plotting and visualization
• TensorFlow — deep learning framework
• scikit-learn — classical machine learning algorithms

Segments / Topics

• Data preprocessing — cleaning, feature engineering, scaling
• Regression — linear, regularized, and polynomial models
• Classification — logistic, SVM, tree-based models
• Clustering — K-Means, hierarchical, DBSCAN
• Reinforcement Learning — policy/value methods, environments
• Natural Language Processing — tokenization, embeddings, sequence models
• Deep Learning — CNNs, RNNs, transformers
• Dimensionality Reduction — PCA, t-SNE, UMAP
• Model Selection & Boosting — cross-validation, hyperparameter search, XGBoost/LightGBM

-+++++++++-+-