Ames Housing Market Analysis: ML & CRISP-DM. Predict Iowa home prices using Kaggle dataset. Apply data science techniques: cleaning, feature engineering, regression modeling. Ideal for aspiring analysts and ML enthusiasts. Includes Jupyter Notebook, blog, visualizations. #DataScience #MachineLearning #RealEstate
A data-based approach to analyse and compare prices and characteristics of Airbnbs listings in Montreal and Toronto and identify the key factors affecting their prices.
Case study for dataset (Violence in USA, 90`). Combination of socio-economic data with FBI stats. Models: PCA, Clustering, Multiple regression. Methodology CRISP DM
Predicting if a NBA rookie player will last at least 5 years in the league
A summative coursework for CSC8631 Data Management and Exploratory Data Analysis
A simple linear regression machine learning model for predicting the total cases of pandemic from OWID dataset. Built using Python libraries (Pandas, NumPy, Statsmodels, Pickle, Matplotlib, Seaborn). Model is further represented as a Flask Web Application with a backend database connectivity to SQLite3 using SQLAlchemy. Later deployed to Heroku …
Online Transaction Fraud Detection using Machine Learning along with Web app creation using Streamlit and deployed on Heroku
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