Hi there! As part of my ongoing course at General Assembly Singapore, I have worked on 5 projects using Python to create predictive analytics data models, using supervised and unsupervised machine learning algorithms.
All my projects will be created using Jupyter technical notebooks for coding, and here is what I have completed so far -
Project 1- Exploratory Data Analysis on educational data. Feature engineering and dataframe manipulation using Pandas with Tableau data visualization.
Project 2- Linear Regression and regularization for housing data. My 'simple' model was able to account for 92% of the variance in housing prices.
Project 3- Web Scraping, NLP and classification of Reddit posts (including a 'bonus section' of Decision Trees, Sentiment Analysis and latent Dirichlet allocation (LDA) topic modelling). My models were 99% accurate in classifying posts.
Project 4 - Time-series analysis & CARTS models to predict disease spread. The model was effective in predicting the spread of West Nile Virus in Chicago with an AUC-ROC score of 0.79.
Project 5 (Capstone)- Various data query, visualization and machine learning methods applied on a large eCommerce dataset to analyze and predict - customer segmentation, lifetime value, churn risk, customer satisfaction, product recommendations.
If you'd like to learn more about these projects and connect professionally, please feel free to add me on LinkedIn - https://www.linkedin.com/in/sahajchawla/