Update README.md

Author: r0f1

README.md

@@ -313,7 +313,7 @@ Understanding SVM Regression: [slides](https://cs.adelaide.edu.au/~chhshen/teach
 [scikit-multilearn](https://github.com/scikit-multilearn/scikit-multilearn) - Multi-label classification, [talk](https://www.youtube.com/watch?v=m-tAASQA7XQ&t=18m57s).  
 
 #### Signal Processing and Filtering
-[Stanford Lecture Series on Fourier Transformation](https://see.stanford.edu/Course/EE261), [Youtube](https://www.youtube.com/watch?v=gZNm7L96pfY), [Lecture Notes](https://see.stanford.edu/materials/lsoftaee261/book-fall-07.pdf).  
+[Stanford Lecture Series on Fourier Transformation](https://see.stanford.edu/Course/EE261), [Youtube](https://www.youtube.com/watch?v=gZNm7L96pfY&list=PLB24BC7956EE040CD&index=1), [Lecture Notes](https://see.stanford.edu/materials/lsoftaee261/book-fall-07.pdf).  
 [The Scientist & Engineer's Guide to Digital Signal Processing (1999)](https://www.analog.com/en/education/education-library/scientist_engineers_guide.html).  
 [Kalman Filter book](https://github.com/rlabbe/Kalman-and-Bayesian-Filters-in-Python) - Focuses on intuition using Jupyter Notebooks. Includes Baysian and various Kalman filters.  
 [Interactive Tool](https://fiiir.com/) for FIR and IIR filters, [Examples](https://plot.ly/python/fft-filters/).