Generic fake news detector across news domains, using feature engineering. Fully implemented POS tagging, sentiment analysis, emotion detection, topic modelling and named entity recognition.

Python has been used to build and evaluate several machine learning models to predict credit risk.

Exploring different text classification methods

Ensemble classifiers are used and compared to resampling strategies to predict credit risk in this analysis. Tools/technologies used include: Pandas, NumPy, Scikit Learn, imblearn, Jupyter Notebook

In this repo I have built and evaluated several machine learning models to predict credit risk using data you'd typically see from peer-to-peer lending services.

Data analysis on single-cell RNA sequencing using Python