8000 rahmatmamat1 (Rahmatsyah Firdaus) · GitHub
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rahmatmamat1/README.md

Hi 👋, I'm Rahmatsyah Firdaus

A passionate Data Scientist with experience in building end-to-end machine learning projects.

Projects

  1. Credit Risk Calssifier: Develop a credit risk classifier service as an API with BentoML and GCP using XGBoost to predict the likelihood of default and assist credit risk management. Code
  2. AdTracking Fraud Detection: Create a fraud detection model using XGBoost on ad tracking data and deploy it as a service using FastAPI and GCP to detect and prevent fraudulent activity. Code
  3. Customer Churn Prediction: Design and build a customer churn prediction service using Logistic Regression model and deploy as an API with Flask and GCP to 82B8 identify at-risk customers and mitigate the potential loss of revenue. Code
  4. Lung Segmentation on Chest X-Ray Image: Design and develop segmentation model using U-Net Architecture and deploy as an API with Flask and TensorFlow Serving. Code
  5. Occupancy of isolation rooms and ICUs: Designed and implemented a model to predict the occupancy of isolation rooms and ICUs in Jakarta using the ARIMA method to support decision-making in healthcare operations during the COVID pandemic. Code
  6. Movie Recommendation System: Develop a recommendation system using collaborative filtering techniques that improves customer retention and generate revenue. Code
  7. Language Identifier: Building model that can idetify languages using natural language processing techniques and Long Short-Term Memory (LSTM) model. Code
  8. Rainfall Forcasting in Makassar, Indonesia: Forecast the rainfall in Makassar using Neural Network.
  9. Customer Segmentation: Utilize DBSCAN and K-Prototype methods to segment and analyze customer data to identify key segments for targeted marketing strategies. Code
  10. Youtube Trending Videos Analysis: Analyze the trending videos on YouTube by creating visualizations to gain insights into the types of videos that are trending and what keywords are commonly used in their titles. Code

Tools:

  • Library: Numpy, Pandas, Matplotlib, Scipy, Scikit-learn, TensorFlow, Keras.
  • Language: Python, SQL, and R.
  • Deployment: , Flask, FastAPI, BentoML, Docker, and Google Cloud Platform.
  • BI Tools: Tableau, Google Data Studio (Looker Studio), and Microsoft Power BI.

Connect with me:

LinkedIn

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