Project: Learning Rate Investigation

This project investigates the effect of different learning rate decaying strategies on deep neural network training, in terms of both convergence time and final accuracy. MNIST and CIFAR-10 datasets are used as examples. Details of the model framework can be checked in the report appendix and in the github notebooks.

Project Report

Project Slides

Github link