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followers: 9.0 following: 23.0 repos: 56.0 gists: 0.0

Name: Onkar Kota

Type: User

Company: K J Somaiya Institute of Information Technology.

Bio: Tech Enthusiast || Problem Solver || Data Scientist

Location: Mumbai , Maharashtra

Blog: https://linktr.ee/onkar.kota

Hi 👋, I'm Onkar Kota

Data alchemist turning numbers into insights ✨ | Passionate about unraveling the secrets hidden in data 📊 | Transforming complexity into simplicity, one dataset at a time 🧩 | Embracing the power of algorithms to decode the world's mysteries 🌍

My Current Status

🌱 I’m currently learning LangChain and LLM models
👯 I’m looking to collaborate on anything free and open source
🤝 I’m looking for help with Data Science Projects
💬 Ask me about Data Science
📫 How to reach me [email protected]

Connect with me:

GitHub Stats 📈

🏆 Git Profile Trophies

⭐ IDEs/Editors

⭐ Data Visualization Tools

⭐ Machine Learning/Deep Learning

⭐ Languages

⭐ Hosting/SaaS

⭐ Frameworks, Platforms and Libraries

⭐ Design

⭐ Databases

⭐ Version Control

Onkar Kota's Projects

market-basket-analysis-case-study

netflix-subscription-forcasting

no-touch-display-interface-at-edge-iot

Enabling HCI on the Edge: Gesture & Offline Sound Control of kiosks with AI models, hardware optimized with Intel OpenVINO, code optimized with VTune

prediction-using-supervised-learning

python-scripts

A curated list of python scripts for automating your tasks

pythondatasciencehandbook

Python Data Science Handbook: full text in Jupyter Notebooks

retrieval-based-voice-conversion-webui

Voice data <= 10 mins can also be used to train a good VC model!

sign-language-interpreter-using-deep-learning

A sign language interpreter using live video feed from the camera.

speech-emotion-recognition

The neural network model is capable of detecting five different male/female emotions from audio speeches. (Deep Learning, NLP, Python)

stock-market-performance-analysis

I made a real time Sudoku solver using the camera, it looks for the edges of the Sudoku in the frame, extracts it, solves it and overlays the solution on the puzzle itself. For the digit recognition, I used a CNN, trained using Keras with printed characters from the different ubuntu fonts. For the image processing part, I used OpenCV for the edge detection.

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