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Cyddharth-Gupta/README.md

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Striving to become a good Blockchain Engineer ย 


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๐Ÿš€ About Me

I'm a passionate software developer with expertise in web development. I specialize in building elegant and user-friendly web applications using cutting-edge technologies like React, Next.js, and Node.js. With a strong foundation in HTML, CSS, JavaScript and Python. I have hands-on experience in crafting responsive and interactive frontends.

While I excel in web development, I'm also deeply interested in the field of Machine Learning. I'm currently on a learning journey to expand my skills in this exciting domain. Exploring the realms of data science, neural networks, and predictive modeling fascinates me, and I'm eager to apply ML techniques to solve real-world problems.

computer I'm currently ...

  • ๐Ÿ’ผ Currently working at DivineTalk Astrology.
  • ๐ŸŒฑ Iโ€™m currently learning about advanced ML algorithms and frameworks like TensorFlow and PyTorch.
  • ๐Ÿ”ญ Iโ€™m looking to collaborate on open-source web projects and ML-related challenges.
  • ๐Ÿ’ฌ Ask me about anything related to web development or my ML learning journey!

๐Ÿ› ๏ธ Technologies & Tools

Web Development

JavaScript React Next.js Node.js HTML5 CSS3 Git GitHub VS Code

Machine Learning

Python NumPy Pandas PyTorch Scikit-learn Scikit-learn AWS

๐Ÿ“ˆ GitHub Stats

Siddharth's GitHub Stats]

๐Ÿ†GitHub Trophies

๐Ÿ“š Featured Repositories

Video Chat App

This repository contains a real-time video chat application built using the MERN stack (MongoDB, Express, React, Node.js) and WebRTC. The app leverages the power of WebRTC for real-time peer-to-peer video and audio communication, and Socket.io for enabling the signaling process between peers. The TCP/IP and UDP concepts are used to establish and manage connections during the video chat sessions.

Weight Category Prediction using Random Forest

This repository contains a machine learning project that predicts weight categories based on various input features using the Random Forest algorithm. The Random Forest model is trained on a labeled dataset containing height, age, and other relevant attributes to classify individuals into different weight categories (e.g., underweight, normal, overweight, and obese). The project aims to provide accurate weight category predictions and facilitate better understanding of the factors contributing to weight classification.

๐Ÿค Let's Connect

I'm always open to interesting discussions and collaboration. Feel free to connect with me on :
Linkedin Twitter.

Looking forward to learning and growing together! ๐Ÿ˜„

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