Name: Faraz Rahman
Type: User
Bio: :wave: Hello, My name is Faraz Rahman
:nut_and_bolt: I am a Mechanical Engineer turned Data Scientist.
:computer: I love to code in Python and R Programming
Location: San Francisco Bay Area
Blog: www.linkedin.com/in/faraz-rahman-0a728a16
Faraz Rahman's Projects
Repository for Jupyter Notebook examples associated with the NASA ARSET Training, "Fundamentals of Machine Learning for Earth Science"
Explore Bikeshare data in R
EDA of dates and time using derived metrics method
A repository listing out the potential sources which will help you in preparing for a Data Science/Machine Learning interview. New resources added frequently.
This project is about building a local database, using DDL and DML to create, load, query, and manipulate database tables and views. Developing a web service to expose the database table for further analysis and use.
Currently working on developing a diabetes prediction application
CMU summer preparation data structures and algorithms assignment
My Open Source Project to create data fetch scripts from open APIs that provide earth observation datasets. This Project was presented at Carnegie Mellon University (Spring 2023)
Employee churn prediction using logistic regression
To assess the welfare of KIVA borrowers(an international nonprofit organization, with a mission to connect people through lending to alleviate poverty)
Predicting car pricing for a company trying to enter the market, based on the available data on car companies in the US
My first Kaggle kernel
building fun Machine Learning projects and practice skills like exploratory analysis, feature engineering, cross-validation techniques and machine learning algorithms
A data engineering pipeline to fetch and parse data from NCBI for further use in analytics.
Getting started with Numpy in Python
Working on SparkR on AWS EMR cluster
GHC Open Source Day (OSD)
Building a Beer RecommenderSystem in R
for participants in the September 2021 DataDive event
My technical Python project on accessing, retrieving and parsing DNA sequencing data that I presented at WiDS 2023, Seattle, April'2023
ML based web app deployed on streamlit for predicting heart diseases. This end-to-end Data Science+Product Management project was presented at Carnegie Mellon University (Fall'2023)
Web parsing in python.
Analysis of Building energy efficiency data