🎓 Aspiring Data Scientist & Machine Learning Engineer | 📍 Bengaluru, India
I'm passionate about transforming data into meaningful insights using Machine Learning, Python, and Data Analytics. I enjoy building end-to-end ML applications with interactive frontends, REST APIs, and deployment using modern tools like FastAPI, Streamlit, and Docker. I'm continuously learning and building real-world projects to strengthen my AI and software development skills.
- Python
- SQL
- Pandas
- NumPy
- Scikit-learn
- Matplotlib
- Seaborn
- Streamlit
- FastAPI
- Docker
- Git & GitHub
- Jupyter Notebook
- VS Code
- Machine Learning
- Statistics
- Data Analysis
- Data Visualization
- Object-Oriented Programming (OOP)
- REST API Development
Predicts whether a customer will churn using a Random Forest Classifier with 85% accuracy. Deployed using Streamlit for interactive predictions.
Tech Stack:
Python • Pandas • Scikit-learn • Random Forest • Streamlit
Predicts diabetes risk from medical inputs using Logistic Regression. Built with an interactive Streamlit interface.
Tech Stack:
Python • Pandas • Logistic Regression • Streamlit • PIMA Dataset
Predicts whether an employee is likely to leave the company using Logistic Regression with a user-friendly Streamlit interface.
Tech Stack:
Python • Pandas • Scikit-learn • Logistic Regression • Streamlit
Segments retail customers using K-Means Clustering and RFM Analysis to identify valuable customer groups.
Tech Stack:
Python • Pandas • Scikit-learn • K-Means • RFM Analysis • Streamlit
An end-to-end restaurant analytics dashboard featuring Exploratory Data Analysis (EDA), Customer Segmentation, Sales Prediction, and a Recommendation System.
Tech Stack:
Python • Pandas • Scikit-learn • Streamlit • Plotly • K-Means • Random Forest • EDA
Predicts whether a loan application will be Approved or Rejected using a Random Forest Classifier. This project demonstrates an end-to-end Machine Learning deployment with a FastAPI REST API, Streamlit frontend, and Docker for containerized deployment.
- Loan approval prediction using Machine Learning
- FastAPI REST API for model inference
- Interactive Streamlit web interface
- Dockerized deployment
- Real-time predictions
Tech Stack:
Python • Pandas • NumPy • Scikit-learn • Random Forest • FastAPI • Streamlit • Docker
- 💻 GitHub: https://github.com/nithinreddyp2004
- 💼 LinkedIn: https://www.linkedin.com/in/reddy-nithin-p/
- 📧 Email: nithinreddyp62@gmail.com
⭐ Feel free to explore my repositories and leave a ⭐ if you find something useful!