Notebooks for data analysis
- Feature Engineering --> Tweet Analysis
- Exploratory Data Analysis (Geo Pandas) and Data Visualization --> Sales Data Analysis, also involves evaluating Key Performance Indicators
- End to End ML Case Study (involves data cleaning, data wrangling, data visualization, feature engineering, model selection and hyper parameter tuning, results and insights) --> Heart Disease Prediction
- ML Case Study using unsupervised learning as well to extract features--> Auto Insurance Claim Prediction
- Marketing Analytics 101 ongoing* (includes evaluating KPIs, segmenting customers (RFM, Lifetime Value, Churn Rate), simulating A/B testing, product recommender system and time series analysis)
- K Means Clustering and PCA a primer
-
For Exploratory Data Analysis tutorial check out the Jupyter Notebooks: 1) Energy Star Prediction inspired by Will Koehrsen; 2) Titanic inspired by jkarakas
-
For ML tutorial check out the Jupyter Notebook titanic-prediction inspired by Niklas Donges at https://github.com/karanm14/EDA-and-Sample-Analysis