Ernest Jack Raju Banothu

Results-driven individual with a solid track record in delivering quality work. Known for excellent communication and teamwork abilities, with a commitment to achieving company goals and delivering exceptional service. Passionate about continuous learning and professional development.

• Eye classification disease using ViT

Python, PyTorch/TensorFlow, OpenCV, Vision Transformer (ViT), NumPy, Matplotlib, Scikit-learn

Developed a deep learning model leveraging Vision Transformers (ViT) to classify retinal fundus images into multiple eye disease categories (e.g., diabetic retinopathy, glaucoma, AMD).

• “Stock Market Forecasting using LSTM Neural Networks

Python, scikit-learn, yfinance, matplotlib

Developed a deep learning model using Long Short-Term Memory (LSTM) networks to forecast stock prices based on historical time-series data. The model captures temporal dependencies and nonlinear patterns in stock price movements to predict future closing prices with improved accuracy over traditional methods.

• Air Quality Forecasting using Machine Learning

Python, Scikit-learn, XGBoost, Pandas

Analyzed and predicted air quality index (AQI) using regression models on environmental sensor data. Engineered temporal and pollutant-based features, performed hyperparameter tuning, and visualized trends using matplotlib and seaborn. Achieved >85% R² accuracy.

• Qualified in the national-level e-quiz competition in mathematics organized by the Ramanujan Maths Club of CBIT
• Proposed one project patent on eye classification disease using MViT in AICTE Idea Lab, CBIT
• Organized a poster presentation event as a coordinator in Sudhee 2025

• Oracle Certified Foundations Associate

certified on April 22, 2025

• Machine learning with Python, IBM

certified on July 12, 2024

• Foundations of cybersecurity, Google

certified on July 17, 2025