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analysis-of-yellow-trip-data-using-hive

This is a an analysis of yellow taxi trip data using Hive

automobile-prediction-case-study-using-simple-linear-regression

This is a simple linear regression example. In the case study, the focus is more on cleaning the categorical data for expression errors and exploratory data analysis as well as feature selection based on the automated techniques and how business knowledge is essential to take an informed decision while performing feature selection.

clustering-countries-basing-on-socio-economic-and-health-factors-

A detailed exercise for beginners in ML. This will comprehend implementation of clustering along with PCA and Outlier treatment extensively

gramener-case-study---lc-loan-approval

A detailed notebook on how to do exploratory data analysis for beginnners. This is an extensive notes on different uni and bivariate analysis even when we limit ourselves to bar plots and histograms

house-price-prediction-with-regularization

This work is similar to Car price Prediction example we detailed earlier but with regularization. The focus is largely on choice of as few as possible features from a large dataset which can explain maximum variance in the data.

lead-scoring-classification-case-study

A Classification Study to predict whether a lead is a potential customer or not. In this study, the focus is largely on thoroughly exploring data on categorical as well as continuous data. We also focused on imputing data using the EDA performed.

market-mix-modeling

sentiment-analysis-on-restaurants-in-bangalore-a-multinomial-classification-using-nlp

This Case Study is a Sentiment Analysis on restaurants in Bangalore using the zomato food reviews (

telecom-churn-prediction-case-study

This is an elaborate attempt to solve an end to end problem statement. In this work, we elaborately worked on outlier treatments, PCA for feature reduction, extensive feature engineering and also impact of features as it is on predictions. This work is an attempt to imitate an industry setting where we solve end to end data science problem except for the data collection part.

uber-supply-demand-gap-a-guide-to-beginner-for-analysisthrough-visualization

A guide to beginner: How to perform uni-variate and bi-variate analysis. In this work, we focused on robust feature engineering from date and time. The date is solely time log data