Explorations in Deep Learning
A collection of deep learning projects exploring computer vision, generative models, natural language processing, and drug discovery.
Other DL Projects I’ve Worked On!
Outside of my primary research, I’ve worked on a variety of deep learning projects that span computer vision, generative models, natural language processing, and predictive modeling in drug discovery. These projects allowed me to experiment with different architectures and techniques while exploring the capabilities of deep learning in unique applications.
1. CNNs for American Sign Language Recognition
I developed a convolutional neural network (CNN) to classify hand gestures representing American Sign Language (ASL). This project demonstrated the ability of CNNs to identify complex patterns and shapes in images, contributing to more accessible communication tools.
- GitHub Repository: CNNs for American Sign Language Recognition
- Notebook: Hand Gesture Recognition
2. GANs for Generating Horse Photos
In this project, I used Generative Adversarial Networks (GANs) to create realistic images of horses. It was a fascinating experiment in unsupervised learning and an opportunity to delve into the nuances of GAN architecture for generating visually plausible data.
- GitHub Repository: GANs for Horse Photos
- Notebook: Generating Horse Photos
3. NLP for Spam Detection
For this project, I worked on a Natural Language Processing (NLP) model to detect spam messages. Using sequential data techniques, this model categorizes messages with a high degree of accuracy, providing a practical application of NLP in filtering communication channels.
- GitHub Repository: NLP for Spam Detection
- Notebook: Spam Detection
4. Drug Discovery Hackathon: Predicting Kinase Selectivity
In Valence Labs’ Machine Learning for Drug Discovery hackathon, I developed a model to predict kinase selectivity, specifically working on the V560G mutant. Competing alone, I placed 8th for this mutant, a rewarding outcome in a field where most participants worked in teams. This project was an exciting application of machine learning in drug discovery.
- GitHub Repository: MLDD Hackathon
- Leaderboard: Polaris Hub - PKIS1 KIT WT MUT C-1
This collection of projects reflects my enthusiasm for exploring diverse aspects of deep learning beyond my core research. From computer vision and generative models to NLP and drug discovery, these projects have broadened my skill set and deepened my appreciation for the versatility of deep learning.