No description
| Backpropagation.ipynb | ||
| Fitting_the_distribution_of_heights_data.ipynb | ||
| Gradient_descent_sandpit.ipynb | ||
| GramSchmidtProcess.ipynb | ||
| IdentifyingSpecialMatrices.ipynb | ||
| PageRank.ipynb | ||
| PCA_week1.ipynb | ||
| PCA_week2.ipynb | ||
| PCA_week3.ipynb | ||
| PCA_week4.ipynb | ||
| README.md | ||
| ReflectingBear.ipynb | ||
| sandpit.ipynb | ||
| sandpit2.ipynb | ||
Mathematics for Machine Learning
This repository contains the code for all the programming tasks of the Mathematics for Machine Learning courses taught at Coursera by Imperial College London:
Linear Algebra (link)
Multivariate Calculus (link)
- The Sandpit
- The Sandpit 2
- Backpropagation
- Gradient descent in a sandpit
- Fitting the distribution of heights data
PCA (link)
- Mean/Covariance of a data set and effect of linear transformation
- Distances and Angles between Images along with KNN implementation
- Orthogonal Projections
- PCA
I've posted the answers here with the intent that it helps with debugging your own. I encourage you not to copy from the resources, but to understand why your code/answers might not have worked. The discussion forums are really helpful, and I recommend asking for help there before using the resources posted here.