Code for "Training models when data doesn't fit in memory" post

Build end-to-end Machine Learning pipeline to predict accessibility of playgrounds in NYC

MLOps Case Study

plagiarism detector that examines a text file and performs binary classification; labeling that file as either plagiarized or not, depending on how similar that text file is to a provided source text. Detecting plagiarism is an active area of research; the task is non-trivial and the differences between paraphrased answers and original work are …

Showcase of MLflow capabilities

The work shown in this repository is part of the Udacity scholarship program in collaboration with Microsoft for Machine Learning Engineer Nanodegree.

In the first course of Machine Learning Engineering for Production Specialization, you will identify the various components and design an ML production system end-to-end: project scoping, data needs, modeling strategies, and deployment constraints and requirements; and learn how to establish a model baseline, address concept drift, and prototype…

🔥🔥🔥🔥🧊🔥🔥 A Data Platform for Monitoring and Detecting Anomalies in Real-Time.

Kafka variant of the MLOps Level 1 stack

A task queue enabling websites to serve ML models -- with RabbitMQ, Celery, all the good stuff.

This neural network can help determine the correspondence of the attached video topic to the video topics recommended by YouTube.

Classification of scientific articles from Frontiers publisher. Deployment ready. Usable as template for text-classification use-cases.

All About ML Engineering

Scaffolding for serving ml model APIs using FastAPI

Notes for Machine Learning Engineering for Production (MLOps) Specialization course by DeepLearning.AI & Andrew Ng

Vehicle data classification (supervised, unsupervised learning)

A project to build an ETL pipeline and ML application to help respond to disaster events faster

Detecting News Generated by LLMs

An easy-to-use tool for making web service with API from your own Python functions.

UniTrends: Using Telegram API, Kafka, and AWS tools to analyze VISA group chats, refining my YouTube content strategy and gained 10k subscribers through data-driven insights.