Unravel the complexities of non-linear dimensionality reduction by mastering t-SNE, geared towards unveiling hidden patterns in multifaceted datasets.
Overview
Syllabus
- Lesson 1: Exploring t-SNE for Dimensionality Reduction in Machine Learning
- Lesson 2: Mastering t-SNE Parameter Tuning in Scikit-learn
- Lesson 3: Exploring Locally Linear Embedding: A Dimensionality Reduction Technique
- Lesson 4: Understanding and Implementing Kernel PCA with sklearn
