Machine Learning (NLP) for Protein Prediction
Sep 2022 - Apr 2023
Machine Learning
Modelled protein sequence distribution to predict results
- Implemented simple RNN and LSTM models for baseline predictions
- Adapted large scale language models from literature
- Technologies used: Pytorch, Tensorflow, Tensorboard
Data Engineering
Cleaned and wrangled data from public scientific databases
- Engineered features and feature embeddings
- Produced visualizations to communicate findings
- Used Pandas, Numpy, and other data science frameworks extensively
Project Management
Planned and organized eight month timeline for project design for a team of four
- Facilitated AGILE and SCRUM meetings to ensure coordination
- Conducted prioritization of features to ensure on time delivery of project deliverables
- Achieved results working independently to ensure critical pieces are in place for other team members