Scalable Machine Learning and Deep Learning, Final Project, 2023/2024

Fraudfinder: A comprehensive lab series on how to build a real-time fraud detection system on Google Cloud

This provider contains operators, decorators and triggers to send a ray job from an airflow task

Designing your first machine learning pipeline with few lines of codes using Orchest. You will learn to preprocess the data, train the machine learning model, and evaluate the results.

Machine Learning Pipeline to categorize emergency messages based on the needs communicated by the sender.

To learn about the key components of MLOps, APIs and API designs.

Created Disaster response pipelines and Web App for classifying text messages received during disaster into response categories, reducing the potential reaction time of disaster response organizations.

"End-to-End Machine Learning Pipeline Creation Using DVC: A comprehensive MLOps solution on GitHub." This GitHub repository showcases the implementation of an end-to-end machine learning pipeline using DVC (Data Version Control) for efficient data management and MLOps practices. The pipeline covers the entire machine learning workflow.

Ds mL starter

Clustering-based ML on the stock dataset using Kmeans, DVC, and MLflow

This project explores how AutoML simplifies machine learning workflows by automating model selection, hyperparameter tuning, and evaluation, comparing tools like TPOT, H2O, and AutoKeras, and culminating in a custom-built AutoML system from scratch.

머신러닝 엔지니어 실무

A Sagemaker e2e multi-model pipeline that can tune multiple models on separate datasets and deploy them to a single endpoint.

The Loan Status Prediction Model predicts loan approval based on applicant details like income, credit history, and loan amount. It uses data preprocessing, an SVC model, and achieves around 79% accuracy. The trained model is saved for future use.

Data Science, Applications and Pipelines

This project based on car price prediction using a Random Forest model and a Streamlit web app for a user-friendly interface.

Master's machine learning projects

Here we create a ML Pipeline that applies transformation to columns of a dataset and then a Linear Regression. Finally we estimate the error and compare the transformed and raw data to check if the pipeline is in fact improving the model.

Predicting Startup Acquisition Statuses using Machine Learning Pipelines!