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About Me

Hello! I'm Puneet Bajaj, a student at IIT Madras with a passion for technology and software development. This README.md serves as an introduction to who I am and what you can expect to find in my GitHub repositories.

Who Am I?

I'm a dedicated learner and developer with a diverse skill set. My journey in the tech world has been driven by a relentless curiosity and a desire to build solutions that make a difference.

What Do I Do?

My work primarily revolves around:

  • Software Development: I'm proficient in a variety of programming languages, including Python, Java, and Rust. I love creating software solutions that tackle real-world problems.

  • Web Development: I have experience with web development technologies such as HTML, CSS, JavaScript, and popular frameworks like React.js. I also have a knack for crafting beautiful and responsive web interfaces using Bootstrap, Tailwind, and EJS.

  • Data Analysis: I'm skilled in Python libraries like Pandas and NumPy, which I use to extract valuable insights from data. Visualizing data is another forte of mine, with Matplotlib being one of my tools of choice.

  • Deep Learning: I'm actively exploring the exciting field of deep learning and neural networks. You'll find projects in my repository related to neural networks, image recognition, and natural language processing.

  • Database Management: I have experience with SQL for relational databases and MongoDB for NoSQL databases. I can design and manage databases to ensure efficient data storage and retrieval.

  • Back-End Development: My expertise extends to Node.js and Express.js, allowing me to build robust and scalable back-end services for web applications.

What Can You Expect from My GitHub?

In my GitHub repositories, you'll find a diverse collection of projects, including:

  • Web Applications: I've developed web applications using various technologies and frameworks. You'll find projects showcasing my front-end and back-end development skills.

  • Data Analysis: I've worked on data analysis projects where I've used Python to clean, analyze, and visualize data to extract meaningful insights.

  • Deep Learning: I'm actively working on deep learning projects that include neural networks, computer vision, and natural language processing. These projects reflect my passion for the field and my commitment to learning and innovation.

  • Open Source Contributions: I believe in the power of open source and have contributed to several projects. I'm always eager to collaborate with others in the open source community.

I'm continuously learning and evolving, so you can expect my repositories to reflect my growth as a developer.

How to Reach Me

I'm open to collaborations, discussions, and feedback. Feel free to reach out to me via:

Don't hesitate to get in touch if you have any questions, want to collaborate on a project, or just want to connect. I'm excited to engage with fellow developers and learners.

Thank you for visiting my GitHub profile, and I hope you find something interesting and valuable in my repositories. Happy coding and exploring the world of deep learning! 🚀🧠

Puneet Bajaj's Projects

aflplusplus icon aflplusplus

The fuzzer afl++ is afl with community patches, qemu 5.1 upgrade, collision-free coverage, enhanced laf-intel & redqueen, AFLfast++ power schedules, MOpt mutators, unicorn_mode, and a lot more!

api-posting-system icon api-posting-system

"NodePostManager" is a Node.js web app for seamless post management, including adding, deleting, searching, and editing posts. Built with Express.js, Method Override, and UUID, it simplifies content organization for bloggers and content creators.

apna-to-do icon apna-to-do

This repository contains a simple and interactive To-Do web application built using HTML, CSS, and JavaScript. It helps to manage tasks with features like task creation, completion tracking, and task deletion. Start organizing your day and staying productive with this user-friendly To-Do web app.

cat-recognition-system icon cat-recognition-system

FelineFinder is a Python-based recognition system with an impressive 80% accuracy rate. It's easy to use and highly adaptable, allowing you to customize the dataset to recognize other objects too. Whether you're a cat lover or need image recognition for various applications, this is your go-to tool for reliable and versatile recognition.

forest-fire-prediction-system icon forest-fire-prediction-system

Forest Fire Prediction System gives the most accurate predictions of when fire can take place. Project made for Software Engineering Lab 2023.

instagram-reels-scraper-auto-poster icon instagram-reels-scraper-auto-poster

Reels-AutoPilot: Reels-AutoPilot is a powerful GitHub repository that scrapes reels from specified Instagram accounts and automatically posts them to your account. Keep up with the latest content from your favorite creators and effortlessly share it with your followers. Enhance your Instagram presence and grow your account with Reels-AutoPilot!

lxmert icon lxmert

PyTorch code for EMNLP 2019 paper "LXMERT: Learning Cross-Modality Encoder Representations from Transformers".

ootdiffusion icon ootdiffusion

Official implementation of OOTDiffusion: Outfitting Fusion based Latent Diffusion for Controllable Virtual Try-on

planar-color-classifier icon planar-color-classifier

I created a planar color classifier using Python and libraries like Matplotlib, NumPy and SciKit-Learn . This classifier efficiently categorizes data points based on color information in a two-dimensional dataset, providing a valuable tool for various image analysis and classification tasks.

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