Aspiring Data Scientist
I am a Microsoft certified data science professional with 2+ years of work experience in the Indian IT sector
I have completed my B.E. in Computer Engineering from Savitribai Phule Pune University in 2019 and since then I have been working as an Oracle Cloud Analyst at Cognizant.
I have hands-on project experience developing and deploying scalable machine learning models using Regression, Classification, Clustering, and Time-series forecasting and deep learning models using ANN and CNN techniques.
An end-to-end ML application that is used to identify customers who are more likely to be churned based on the historical data provided by the Telco company. The flask application is deployed as a microservice to the Docker registry.
An Unsupervised learning model built for customer segmentation using RFM modelling and K-Means clustering algorithm. The model is built on Online retail store dataset from the UCI ML repository.
An end-to-end ML application to predict the sales of each item at a particular outlet store. The flask application is deployed using AWS EC2 instance.
A supervised ML regression problem to predict the estimated time a taxi takes to reach the entered location in New York City.
An end-to-end ML application to predict the selling price of used cars based on the data provided by cardekho.com.
A supervised ML binary classification model built on an imbalanced dataset to detect if a transaction is fraudulent or not..
A DL model build using Artificial Neural Network that is used to identify bank customers who are more likely to be churned based on the provided historical data.
A multiclass classification model that performs text cleaning, text analysis and classification based on the sentiments.
Step-by-step explanation of the approach to solve the multiclass classification problem including text cleaning, analysis, and classification based on the sentiments.
Docker is an open platform for developing, shipping, and running applications. Docker enables you to separate your applications from your infrastructure to deliver software quickly.
The moving average (MA) is a simple technical analysis tool that smooths out price trends by filtering out the noise from random short-term price fluctuations.
PySpark is a python API for Apache Spark. Using PySpark we can run applications parallelly on the distributed cluster (multiple nodes) or even on a single node.
This post aims to get familiar with the deep learning concepts and apply them to the Churn for Bank Customer dataset from Kaggle. We will predict the bank customers who are most likely to be churned using the Artificial Neural Network (ANN).