Developed by Akhil Devarashetti
Deep Learning Engineer | akhil.ai
This is a master project of some experiments with Neural Networks. Every project here is runnable, visualized and explained clearly.Take a tour
Start your Deep Learning journey with simple problems
Visualize and learn Computer Vision models from basic classifiers to complex vision problems
Learn how neural networks are trained on text
Learn how models are trained to play games from basic to state-of-the-art methods
Abstract: I tried to create a model that simulates the spread of a disease that does not have a medicine. I observed the effects of varying parameters, then introduced a concept of deflections which mimic social distancing and social gatherings. I finally made an attempt to evolve these deflections based on a performance metric.
Abstract: Deep Reinforcement Learning is a branch of machine learning techniques that is used to find out the best possible path given a situation. It is an interesting domain of algorithms ranging from basic multi-arm bandit problems to playing complex games like Dota 2. This paper surveys the research work on model-free approaches to deep reinforcement learning like Deep Q Learning, Policy Gradients, Actor-Critic methods and other recent advancements.
Find All Numbers
Style, Please V2
What Genre - Attention
Self-Organizing Feature Maps
MNIST Detection Dataset