Gian Atmaja's Projects
My project portfolio for the Applied Data Science with Python Specialisation in Coursera.
Using machine learning to predict customer churn.
An analysis on a home loan customer base to identify groups leading to good and bad rates. Language: Python
A Tableau dashboard that explores the global digital divide, diving specifically into inclusive internet access around the world, its contributing factors, and events associated with high and low internet inclusiveness.
A proof-of-concept for the implementation of an early fault detection system in oil wells, designed to enhance operational efficiency and reduce costs.
End-to-end pipeline that stores, analyses and classifies the categories of emergency messages.
A classification model on publicly available Census Bureau data, deployed using FastAPI & Render, with CI/CD incorporated using GitHub Actions.
GitHub Profile README
An informative dashboard on global warming, made using R's ggplot2, plotly, and flexdashboard.
This project involves language modelling in Keras, including training models to predict the next word in a sentence, computing sentence likelihood as well as similarity between words.
Life insurance cost of coverage calculator web application using R's shiny
An ML monitoring framework, applied to an attrition risk assessment system.
A reusable ML pipeline that is used to predict short-term rental prices in NYC, based on the property-related features.
Web application to predict the next most likely word.
This project involves feature representation of text data, implementation of perceptron algorithm, as well as gradient descent in Python.
Projects related to statistical modelling in R
This repository contains the projects I completed in the Udacity Data Engineering Nanodegree.
This repository contains the projects I completed in the Udacity Deep Learning Nanodegree.
A reusable codebase for fast data science and machine learning experimentation, integrating various open-source tools to support automatic EDA, ML models experimentation and tracking, model inference, model explainability, bias, and data drift analysis.
An application of the WhizML codebase for an analysis of cardiovascular disease risk.
An application of the WhizML codebase for an analysis of Walmart weekly sales.
React
Typescript
Django
Laravel
Facebook
Microsoft
Google
Alibaba
D3
Tencent