Brain Tumor Segmentation
Developed a U-Net based FCNN model using PyTorch framework to create segmentation maps for brain tumor from brain tumor MRI images.
Developed a U-Net based FCNN model using PyTorch framework to create segmentation maps for brain tumor from brain tumor MRI images.
Built a Python installable package for a custom OpenAI Gym toolkit. Simulates a rocket landing on a pad, modeled after SpaceX Falcon rockets.
Experimenting with Autoencoder architecture to reconstruct MNIST Handwritten Digits & Fashion datasets with visualization of internal network compressed representation.
Implemented Q - Learning Algorithm from scratch using Numpy with understanding its dependency on Dynamic Programming. This algorithm was tested with OpenAI Gym toolkit on ToyText environments.
Implementing a list of well known algorithms for educational purpose. As of now project is still going on, majority of the topics are implemented in Python. In future may implement with Java.