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

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

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.

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.

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

Ds mL starter

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

"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.

머신러닝 엔지니어 실무

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

Data Science, Applications and Pipelines

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!