Data Science

This project is geared toward highlighting the theory and applications for popular traditional Data Science methods that you typically see taught in Undergraduate or Master/PHD programs. This Data Science Github encompasses the current methods I had completed.

Project currently supports the following implementations; Some of these projects are either in R or Python.

• ARIMA
• Bayesian Regression
• Data Imputations
• Data Wrangling
• GRU (Gated Recurrent Unit)
• KNN (K Nearest Neighbor)
• Linear Regression
• Logistic Regression
• Multiple Linear Regression
• Naive Bayes
• Principal Components
• RNN (Recurrent Neural Networks)
• Recommendation Systems
• Sampling Methods
• Visualizations in R
• XGBoost

Natural Language Processing: Python

• Question Answering (QA)
• Transformers
• Bidirectional Encoder Representations (BERT)
• Named Entity Recognition (NER)
• Sentiment Analysis
• Text Preprocessing