This is a project for the course "Linear Algebra" at the University Khaje Nasir Toosi of Technology, Semester 4011.
In this project, we practiced concepts of linear algebra, such as:
- Principal Component Analysis (PCA)
- Singular Value Decomposition (SVD)
- Differentiation
- Gradient Descent
The project compromises of five parts:
- Logistic Regression
- Logistic Regression using Tensorflow
- Multilayer Neural Network
- Principal Component Analysis (PCA)
- Bonus: Linear Discriminant Analysis (LDA)
The full description of the project is available in the file "LA4011-final-project-v3.pdf".
The following packages are required to run the code:
- numpy
- matplotlib
- tensorflow
The project was a great experience for me. I learned a lot about linear algebra and machine learning. I hope you enjoy it too.