I have recently created this page to include my own explanations of several complicated concepts in machine learning. If you learn something from these videos or enjoy watching, then please like and support the individual videos of interest so I can know to produce more contents.
Below are the videos that I have uploaded so far.
Below are the videos that I have uploaded so far.
We look in this video at Approximate entropy, Sample entropy, Fuzzy entropy, Distribution entropy, Permutation entropy and the commonality in their implementations.
- Wavelets & Feature Extraction
- Wavelets & Feature Extraction - Part2 - Wavelet Scattering Transform.
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- Entropy and Mutual Information
- Finding Causal Relationships: Granger Causality vs. Transfer Entropy
- Hjorth Parameters. A feature extraction approach allowing us to retrieve important parameters of the power spectrum directly from the time-domain.
- PCA vs. LDA: An intuitive explanation of the concepts only.
- Long Short-Term Memory (LSTM): An intuitive explanation of the concepts only.
