About me - 13/03/2024
I'm Sanjai a Student from CSE
Description
I am Sanjai, a student studying Computer Science and Engineering (CSE). I have a keen interest and proficient knowledge in various technical skills including Python , Django , Machine Learning and Deep Learning , SQL. I am enthusiastic about utilizing these skills to solve real-world problems and contribute to projects. I am eager to explore opportunities where I can apply my expertise and continue to learn and grow in the field of technology.
Skills
- Python
- Django
- Machine Learning and Deep Learning
- Gen AI
- JavaScript (Basics)
- HTML
- CSS
- Java(Basics)
- Data Structures and Algorithms (DSA)
- AWS(Basics)
- Cloudflare
- Scikit Learn
- Git and Github
- Selenium(Basics)
Projects
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Blog Application with User Authentication
Created a feature-rich blogging platform where users can write, edit, and delete posts. Integrated authentication (signup, login, logout) and user profile management. Added a comment system and like functionality using Django models.
Tech Stack: Django, Python, Bootstrap, mySql
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Real-Time Chat Application
Developed a real-time chat system where users can communicate instantly. Implemented one-on-one messaging, group chats, and chat history storage. Used Django Channels and WebSockets to enable real-time message exchange. Integrated user authentication, online status indicators, and message notifications.
Tech stack Django, Django Channels, WebSockets, JavaScript, SQLite
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HoardView
Developed an AI Application made with Computer vision and Neutral Network that used to detect illegal hoarding boards in the major cities and report to authorities. Helps to learn new technologies that made me learn empower in the emerging
technologies in the competitive fields.
Tech stack Python,Hugging Face,TensorFlow,tesseract,computer vision.
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Traffic Sign Board Detection Using CNN
This project demonstrates the effectiveness of CNNs in traffic sign recognition. The developed model shows high accuracy reliable classification across various traffic sign categories. Future improvements could focus on optimizing the model for deployment in real-time autonomous driving systems.