An open-source data logging library for machine learning models and data pipelines. 📚 Provides visibility into data quality & model performance over time. 🛡️ Supports privacy-preserving data collection, ensuring safety & robustness. 📈

An open-source ML pipeline development platform

Free Open-source ML observability course for data scientists and ML engineers. Learn how to monitor and debug your ML models in production.

An AutoML pipeline selection system to quickly select a promising pipeline for a new dataset.

Free and open source automation platform

Library for streaming data and incremental learning algorithms.

Best practices for engineering ML pipelines.

Components that I have created for Kubeflow Pipelines. Try them in https://cloud-pipelines.net/pipeline-editor/

Fraud detection ML pipeline and serving POC using Dask and hopeit.engine. Project created with nbdev: https://www.fast.ai/2019/12/02/nbdev/

This a repo that was created to learn more about Airflow and develop awesome data engineering projects. 🚀🚀

Open source AI platform for rapid development of advanced AI and AGI pipelines.

This Project is a part of Data Science Nanodegree Program by Udacity in collaboration with Figure Eight. The initial dataset contains pre-labelled tweet and messages from real-life disasters. The aim of this project is to build a Natural Language Processing tool that categorize messages.

Website built in JavaScript & React as a "blog" to document an ML pipeline I built for Apartment Price Scraping project

This project focuses on building end-to-end machine learning pipeline using AWS SageMaker to predict the price range of mobile phones based on their specifications, enhancing consumer decision-making and streamlining the development process.

Proving Skills in Pipelines, Pickle Files and ML Modelling

A deployed machine learning model that has the capability to automatically classify the incoming disaster messages into related 36 categories. Project developed as a part of Udacity's Data Science Nanodegree program.

In this project, I developed a completed Vertex and Kubeflow pipelines SDK to build and deploy an AutoML / BigQuery ML regression model for online predictions. Using this ML Pipeline, I was able to develop, deploy, and manage the production ML lifecycle efficiently and reliably.

Course 2 project of the Udacity ML DevOps Nanodegree Program

This repository contains my code solution to DeepLearning.AIs Practical Data Science On AWS Cloud Specialization.

Collaborative team machine learning project classifying reviews scraped from the IMDB website as either positive or negative using sentiment classification. Tools used: BeautifulSoup and Splinter to scrape reviews, Pyspark, SQLAlchemy and Heroku.