📄️ PCA
Mastering feature extraction, variance preservation, and the math behind Eigenvalues and Eigenvectors.
📄️ Autoencoders
Neural network-based dimensionality reduction: Encoder-Decoder architecture and bottleneck representations.
Dimensionality Reduction Techniques
Reduce feature space complexity while preserving important information using techniques like PCA and Autoencoders.