🎓 B.Tech Computer Science & Engineering student at Noida Institute of Engineering and Technology (NIET)

💻 Interested in Software Development, Machine Learning, Data Structures & Algorithms and Database Management

🐍 Currently strengthening my skills in Python, DSA, SQL and Object-Oriented Programming

🤖 Experienced in building projects using Machine Learning, Flask, MongoDB and MySQL

🚀 Interested in developing practical applications that solve real-world problems

🌱 Continuously learning new technologies and improving my problem-solving skills

🎯 Currently preparing for Software Engineering and Technical Placement Opportunities

• Data Structures & Algorithms
• Object-Oriented Programming
• Machine Learning
• Database Management Systems
• SQL & Relational Databases
• REST APIs
• Data Preprocessing
• Exploratory Data Analysis
• CRUD Operations
• Git & GitHub
• Software Development Fundamentals

An AI-powered crop advisory platform designed to provide farmers with data-driven crop recommendations using machine learning and real-time agricultural data.

Technologies:

Python Flask MongoDB Random Forest Streamlit JWT

Key Features:

• 🌱 Crop recommendation using Machine Learning
• 🌦️ Weather and soil data integration
• 🔐 JWT-based authentication
• 👥 Role-Based Access Control
• 📊 Data-driven agricultural insights
• 🔌 REST API based backend
• 🗄️ MongoDB data management

A Machine Learning project that identifies food items from images and provides calorie estimation.

Technologies:

Python Machine Learning Computer Vision Flask

Key Features:

• 🍔 Food image recognition
• 🔍 Image processing
• 📊 Calorie estimation
• 🌐 Application interface
• 🤖 Machine Learning based prediction

🔗 Repository:
https://github.com/kunalbansal07/food-recognition-calorie-estimation

A SQL-based database management system designed to manage students, courses, instructors and enrollments.

Technologies:

MySQL SQL Database Management

Key Concepts:

• CRUD operations
• Primary & Foreign Keys
• Joins
• Views
• Stored Procedures
• Functions
• Triggers
• Indexing
• Database relationships
• ER Diagram

🔗 Repository:
https://github.com/kunalbansal07/Student-Management-System-SQL

A Machine Learning project that groups customers into meaningful segments using the K-Means clustering algorithm.

Technologies:

Python Pandas NumPy Scikit-Learn Matplotlib

Key Concepts:

• Data preprocessing
• Exploratory Data Analysis
• K-Means clustering
• Feature analysis
• Customer segmentation
• Data visualization

🔗 Repository:
https://github.com/kunalbansal07/customer-segmentation-kmeans

A Machine Learning project for predicting house prices using historical housing data.

Technologies:

Python Pandas NumPy Scikit-Learn Machine Learning

Key Concepts:

• Data preprocessing
• Feature engineering
• Regression
• Model training
• Model evaluation
• Prediction

🔗 Repository:
https://github.com/kunalbansal07/HousePricePrediction

Worked on practical Machine Learning projects and gained experience in Python, data processing and model development.

Areas of Work:

• Python programming
• Machine Learning
• Data preprocessing
• Model development
• Computer Vision
• Practical ML applications

• 🐍 Machine Learning using Python
• 🧩 Object Oriented Programming using Python
• 📚 Data Structures using Java

Python
    ↓
Data Structures & Algorithms
    ↓
SQL & DBMS
    ↓
Object-Oriented Programming
    ↓
Machine Learning
    ↓
Backend Development