Update README.md

README.md

@@ -44,7 +44,7 @@ Another application of SVD is to identify the people and remove the background o
   - [Stability of LU](https://nbviewer.jupyter.org/github/fastai/numerical-linear-algebra/blob/master/nbs/3.%20Background%20Removal%20with%20Robust%20PCA.ipynb#Stability)
   - [LU factorization with Pivoting](https://nbviewer.jupyter.org/github/fastai/numerical-linear-algebra/blob/master/nbs/3.%20Background%20Removal%20with%20Robust%20PCA.ipynb#LU-factorization-with-Partial-Pivoting)
 
-### 4. Compressed Sensing with Robust Regression
+### 4. [Compressed Sensing with Robust Regression](http://nbviewer.jupyter.org/github/fastai/numerical-linear-algebra/blob/master/nbs/4.%20Compressed%20Sensing%20of%20CT%20Scans%20with%20Robust%20Regression.ipynb#4.-Compressed-Sensing-of-CT-Scans-with-Robust-Regression)
 Compressed sensing is critical to allowing CT scans with lower radiation-- the image can be reconstructed with less data.  Here we will learn the technique and apply it to CT images.
   - [Broadcasting](http://nbviewer.jupyter.org/github/fastai/numerical-linear-algebra/blob/master/nbs/4.%20Compressed%20Sensing%20of%20CT%20Scans%20with%20Robust%20Regression.ipynb#Broadcasting)
   - [Sparse matrices](http://nbviewer.jupyter.org/github/fastai/numerical-linear-algebra/blob/master/nbs/4.%20Compressed%20Sensing%20of%20CT%20Scans%20with%20Robust%20Regression.ipynb#Sparse-Matrices-(in-Scipy))