iwalwil / digits-classifier

Digits Classifier

Supervised by: Mr. Olivier Fercoq.

Course: Stochastic Optimization.

Programming Language: Python.

Project Description

Each student will be assigned a problem and an algorithm to implement on this problem. We will use the database MNIST http://yann.lecun.com/exdb/mnist/ where the goal is to classify digits between 0 and 9.

The Work to Do

1. Each student chooses a model and an algorithm to determine its parameters.
2. By keeping part of the training set into a validation set, find a good value for the hyperparameters of the model.
3. We will compare models and optimization algorithms in terms of classification performance, quality of the local optima returned by each method, the speed of convergence.

My work

1. The Chosen Model: The Multinomial logistic regression with squared 2-norm regularization .
2. The Chosen Algorithm Stochastic Gradient Descent (SGD)