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Projects in Awesome Lists by ParagGhatage

A curated list of projects in awesome lists by ParagGhatage .

https://github.com/paragghatage/artify

Artify is a Neural Style Transfer project that blends the artistic patterns of a style image with the content of another image using deep learning techniques. It leverages the VGG19 model to extract content and style features, enabling the creation of visually stunning artwork that merges textures, colors, and patterns from different sources.

art computer-vision deep-learning deep-neural-networks machine-learning

Last synced: 18 Dec 2024

https://github.com/paragghatage/portfolio

I am Parag Ghatage, a full stack web developer specializing in Next.js. I developed Explora, a travel planning app that allows users to explore photos, check real-time weather, and plan trips with accommodation and travel options. It uses technologies like Next.js, TypeScript, Tailwind CSS, MongoDB, and various APIs.

Last synced: 18 Dec 2024

https://github.com/paragghatage/paragghatage

Config files for my GitHub profile.

config github-config

Last synced: 18 Dec 2024

https://github.com/paragghatage/thunder-tube

Welcome to Thunder Tube! This project is a YouTube clone designed to replicate core features of YouTube, such as video subscriptions, likes, playlists, comments, channel profiles, and more. Thunder Tube is built using modern web technologies including React.js, Node.js, HTML, CSS, JavaScript, and MongoDB.

Last synced: 18 Dec 2024

https://github.com/paragghatage/explora

Built a travel planning web app enabling users to explore photos, access real-time weather, plan trips with accommodation and travel options, and use interactive maps with live data.

Last synced: 18 Dec 2024

https://github.com/paragghatage/socialspark

Analyzes social media engagement data using DataStax Astra DB and Langflow. Includes mock data, workflows for querying and metrics calculation, and GPT integration for insights.

Last synced: 02 Jan 2025

https://github.com/paragghatage/celestial-descent

Celestial-Descent is a reinforcement learning project designed to develop an intelligent agent capable of landing a spacecraft on the lunar surface. Leveraging the Gymnasium library and Stable Baselines3, this project provides an engaging platform for exploring the fundamentals of reinforcement learning (RL) in a simulated environment.

reinforcement-learning stable-diffusion

Last synced: 09 Dec 2024