Docker for getting jax to work with cuda, for reproducing ml experiments like eicl. Sure, let's NOT make a compatibility matrix and let people fight for their lives on cuda

MLOps project Training and Deployment of Churn prediction model

Python package that simplifies the creation of AWS infrastructure for simulating real-time data streaming and batch processing, ideal for integrating into machine learning projects.

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

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

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.

A library for authoring DLT pipelines via meta-programming patterns and deploying to Databricks workspaces.

MLOps project Training and Deployment of Spacy model for Sentiment analysis

This repository serves as a platform where I share articles and implementations related to various machine learning concepts and projects. Through this blog, I aim to document my learning journey and provide insights into the fascinating world of machine learning.

A simple Python script to check the strength of a password based on length, the inclusion of numbers, special characters, and upper/lower case letters.

Recommendation System for Books using Collaborative Filterings: An ML Project to Recommend 'n' similar Books for a given book, as per the Collaborative users' ratings of the books. This Project also involves the deployment in a Flask Based web application.

⛰️ machine learning pipeline for disaster alert

Detecting News Generated by LLMs

Исследование на тему "Транскодирование изображений JPEG с использованием предсказания коэффициентов ДКП на основе нейронной сети".

DermaDetectAI is a Flask app for detecting skin diseases using deep learning. Developed by Ranit Manik and team, it includes models for identifying 5, 10, and 23 skin conditions, and supports NVIDIA GPU acceleration. The models are trained with PyTorch.

Work-in-progress

Utilizing machine learning techniques, this project predicts vehicle prices based on features like age, fuel type, and more. Models include Linear Regression, Lasso Regression, and Random Forest. Dataset sourced from Kaggle.

Example of a typical Machine Learning engineering problem

Kids Care AI IOT Device - RaspberryPi USB Mic voice detection and Picamera fall detection.

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