class KrushnaSonawane:
def __init__(self):
self.name = "Krushna Khandu Sonawane"
self.location = "Nashik, Maharashtra 🇮🇳"
self.education = "B.E. in AI & Data Science"
self.college = "Guru Gobind Singh College of Engineering"
self.graduation_year = 2026
self.role = "AI & Data Science Student | Python Developer"
def skills(self):
return {
"languages": ["Python", "SQL", "C++", "HTML/CSS"],
"ml_frameworks": ["Scikit-Learn", "NumPy", "Pandas"],
"backend": ["FastAPI", "REST API", "SQLAlchemy"],
"databases": ["MySQL", "SQLite", "SQL Server"],
"tools": ["Git", "GitHub", "Streamlit", "Render"],
"visualization": ["Matplotlib", "Seaborn"]
}
def interests(self):
return ["AI/ML", "Data Science", "Backend Development", "Problem Solving"]
def current_focus(self):
return ["Building ML Projects", "FastAPI Development", "Learning Deep Learning"]
me = KrushnaSonawane()
print(f"👋 Hello! I'm {me.name}, passionate about {', '.join(me.interests())}")
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NetLeap IT & Training Solutions, Nashik | Jan 2025 - Feb 2025
+ Developed ML-powered recommendation system with 90% accuracy
+ Implemented data preprocessing workflows using Pandas & NumPy
+ Built and deployed RESTful APIs using FastAPI
+ Collaborated on problem-solving and project documentation
+ Analyzed data-driven solutions using ML techniques
Tech Stack: FastAPI • React • Groq AI (Llama 3.3 70B) • SQLAlchemy • SQLite
Features:
- Full-stack AI story generator with real-time generation
- Integrated Groq Llama 3.3 70B through REST APIs
- RESTful backend with SQLAlchemy ORM
- Deployed on Render with production-ready setup
Highlights:
- ✅ Real-time AI story generation
- ✅ Modern React frontend
- ✅ Scalable FastAPI backend
- ✅ Cloud deploymentTech Stack: Python • Pandas • NumPy • Scikit-Learn • Collaborative Filtering
Features:
- Hybrid recommendation using collaborative + content-based filtering
- Analyzed 10,000+ songs dataset
- Modular ML pipeline for preprocessing and training
Achievements:
- 🎯 90% recommendation accuracy
- 📊 Advanced feature extraction
- 🔧 Model tuning & optimization
Tech Stack: FastAPI • Scikit-Learn • Pandas • Streamlit
Features:
- ML-powered car price prediction API
- Interactive Streamlit frontend
- RESTful API endpoints
- Real-time predictionsTech Stack: FastAPI • SQLAlchemy • PostgreSQL • JWT Authentication
Features:
- Complete e-commerce backend
- User authentication & authorization
- Product management CRUD
- Order processing systemTech Stack: Python • Sentinel-2 • Geospatial Analysis
Features:
- Satellite imagery analysis
- Geospatial data processing
- Environmental monitoring| 🔥 GitHub Streak | |
| 📅 Current Streak | 🏆 Longest Streak |
| Active Developer | Building Daily |
| 📊 Total Contributions | |
| Check GitHub Graph Below ⬇️ | |
| 🎓 Certification | 🏢 Organization | 📅 Date |
|---|---|---|
| AI-ML Virtual Internship | EduSkills | 2024 |
| Data Science Virtual Internship | TCS iON via Forage | Dec 2024 |
| 90% ML Model Accuracy | NetLeap IT Solutions | Jan 2025 |
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mindmap
root((Krushna<br/>Sonawane))
Machine Learning
Regression
Classification
Feature Engineering
Model Evaluation
Backend Development
FastAPI
REST APIs
SQLAlchemy
Authentication
Data Science
EDA
Statistics
Hypothesis Testing
Data Visualization
Tools & Tech
Git/GitHub
SQL Databases
Streamlit
Cloud Deployment
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| 🚀 Projects & Code | 🧠 Knowledge Base | 💼 Experience |
|---|---|---|
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| 🏆 Achievement | 📝 Description | ✅ Status |
|---|---|---|
| ML Master | Built ML model with 90% accuracy | Completed |
| API Developer | Created multiple FastAPI projects | Completed |
| Full Stack | Built complete AI story generator | Completed |
| Data Scientist | Completed TCS & EduSkills internships | Completed |
| Problem Solver | Solving real-world problems with code | In Progress |
