Machine Learning
161 learners
Non-linear Dimensionality Reduction Techniques
Unravel the complexities of non-linear dimensionality reduction by mastering t-SNE, geared towards unveiling hidden patterns in multifaceted datasets.
MatPlotLib
Numpy
Python
Scikit-learn
See path
4 lessons
13 practices
3 hours
Badge for Feature Engineering,
Feature Engineering
Lessons and practices
Visualizing the Iris Dataset with t-SNE
Explore the 3D Space with t-SNE
Implementing t-SNE Visualization on Iris Dataset
Visualizing Clusters with t-SNE
Exploring the Perplexity of t-SNE
Tuning the Stars: Adjusting t-SNE Parameters
Space Voyage: Apply and Visualize t-SNE on the Digits Dataset
Unfolding the Swiss Roll with LLE
Adjusting the Number of Neighbors in LLE
Squish the Cosmic Data: Tuning LLE Parameters
Kernel PCA: Visualizing Transformed Data and Calculating Reconstruction Error
Exploring Kernel Functions in Kernel PCA
Kernel PCA: Uncover the Hidden Patterns
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