Rajdeep Biswas's Projects
MLOps with Azure ML
Hacking to enable and build modern datawarehouse
A fast & minimal Jekyll blog theme with clean dark mode
The Movies dataset is extraordinarily rich in nature and a lot of interesting data science and exploratory data analytics analysis can be done using it. In this project I have created a movies data consortium by blending a file data store sourced from the Movies Dataset hosted in Kaggle, website data from Wikipedia and API data from themoviedb.org.
Production data from New Mexico is published each month in a zipped, 36 GB XML file. It contains data for 55,000 wells over the past 30 years. The file grows in size by 300 MB per month. This repository uses spark code to process the file.
Exploratory Data Analytics on New York Taxi (NYC) Dataset
Simple tutorial on Python Exception Handling
Config files for my GitHub profile.
contains exe for the iot simulator
This project would demonstrate the following capabilities: 1. Extraction Loading and Transformation of S&P 500 data and company fundamentals. 2. Exploratory and Time Series Data Analysis on top of the stock data. 3. Stock Screener based on fundamentals. 4. Stock Price Prediction using multiple and/or an ensemble of machine learning models.
Scrub the stock related news and perform sentiment analysis on top of that.
We will analyze the results of a survey recently given to college students. The research question being investigated is: βIs there a significant relationship between the amount of time spent reading and the time spent watching television?β You are also interested if there are other significant relationships that can be discovered? The survey data is located in StudentSurvey.csv file.
Text and supporting code for Think Stats, 2nd Edition