Update README.md

README.md

@@ -2,3 +2,5 @@
 redsvd is a library for solving several matrix decompositions including singular value decomposition (SVD), principal component analysis (PCA), and eigen value decomposition. redsvd can handle very large matrix efficiently, and optimized for a truncated SVD of sparse matrices. For example, redsvd can compute a truncated SVD with top 20 singular values for a 100K x 100K matrix with 1M nonzero entries in less than one second.
 
 The algorithm is based on the randomized algorithm for computing large-scale SVD. Although it uses randomized matrices, the results is very accurate with very high probability. See the experiment part for the detail.
+
+<img src="https://raw.githubusercontent.com/andrewssobral/redsvd/master/images/project_info.png" width="250">