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πŸ‘‹ Hey there, I'm Cyril!

πŸ”­ I’m currently working on implementing the knowledge of AI in various fields
πŸ‘― I’m looking to collaborate on AI & ML projects
🀝 I’m looking for help with hackathon preparation
🌱 I’m currently learning Flutter and DSA
πŸ’¬ Ask me about my internship experience
⚑ Fun fact: I like to practice competitive programming on CodeChef

🌐 Socials: X (formerly Twitter) Medium)

πŸ’» Tech Stack:

Dart C C++ HTML5 Python CSS3 Google Cloud Firebase Vercel GithubPages Flutter OpenCV MongoDB MySQL SQLite Canva Figma Adobe Lightroom Pandas NumPy Matplotlib Git GitHub

πŸ“Š GitHub Stats:



πŸ† GitHub Trophies

✍️ Random Dev Quote

πŸ” Top Contributed Repo



Snake animation

Cyril Jacob's Projects

cj445 icon cj445

Config files for my GitHub profile.

codsoft icon codsoft

This repo contains the source code of all the tasks accomplished as part of my internship at CodSoft. Each project has its own repository and has been added as a submodule in this repository as well.

face-mask-detection icon face-mask-detection

Face Mask Detection using NVIDIA Transfer Learning Toolkit (TLT) and DeepStream for COVID-19

face-recognition icon face-recognition

An AI application detects and recognizes faces in images or videos using pre-trained models like Haar cascades. It allows for real-time identification and labeling of registered faces.

nihory-basic icon nihory-basic

Nihory is a creative 🌈 personal & portfolio template based on HTML, CSS and Javascript. You can use it for your personal resume, CV or your portfolio. It will help you to present your self even your Business & portfolio more smartly and easily. Nihory is written in valid and clean HTML & CSS3 code. It’s easy to customize πŸ–Œ

sign-language-detection-using-pose-sequential-rnn icon sign-language-detection-using-pose-sequential-rnn

This project focuses on classifying the users actions into one of the three which consists of 'please', 'hello' and 'thank you' which can help people understand other people with speech or hearing disabilities. The project uses Pose Estimation with the help of Mediapipe Holistics and an RNN model which helps to get an accuracy around 99% accuracy.

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