A case study to determine whether a new feature should be added to the Yammer website after analyzing A/B test results.
My take on Possible consequences of decisions algorithms make on our behalf.
This project deals with many real-world challenges faced by e-commerce websites that includes predicting customer lifetime value using RFM score and k-means clustering, customer segmentation to find out best valued customers. Also, predicting review score the customers will give to their order experience depending on their location, order cost and other factors.
Audio Classification using raw waveforms, extracted features and feature learning.
An article explaining Convolutional Neural Network for absolute beginners.
This project analysis the current trends and attitude of the employers towards the mental health. It also presents the classifier models to identify how likely it is that an employee will seek the treatment for the mental health issues.
In this project, I am using my Data Engineering skills to analyze disaster data from Figure Eight. The classifier model is built using Extract, Transform and Load process(ETL), natural language processing(NLP) and machine learning pipeline for classifying disaster messages. The project also includes a web app where an emergency worker can input a new message and get classification results in several categories.