GitHub / chandlergibbons / Machine-Learning-Medical-Transcription-Project

For our final project, our group chose to use a dataset (from Kaggle) that contained medical transcriptions and the respective medical specialties (4998 datapoints). We chose to implement multiple supervised classification machine learning models - after heavily working on the corpora - to see if we were able to correctly classify the medical specialty based on the transcription text.

JSON API: http://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/chandlergibbons%2FMachine-Learning-Medical-Transcription-Project
PURL: pkg:github/chandlergibbons/Machine-Learning-Medical-Transcription-Project

Topics: doc2vec, gensim, gridsearchcv, hyperparameter-tuning, machine-learning, machine-learning-algorithms, matplotlib, naive-bayes, nltk, numpy, pandas, pca-analysis, plotly, randomforest, scikit-learn, tfidfvectorizer, yellowbrick

• Files
• Readme
• Dependencies