NABINNEPALI

Developed a secure RESTful API using FastAPI with MongoDB for a to-do list application. Implemented full CRUD operations, user authentication with JWT tokens, and password hashing for enhanced security.

Built a time series forecasting model using SARIMAX to predict energy consumption patterns. Implemented data preprocessing, model training, and evaluation with confidence intervals for predictions.

Developed a convolutional neural network using PyTorch for binary classification of cat and dog images. Achieved high accuracy through data augmentation, transfer learning, and hyperparameter tuning.

Created a command-line test management system for organizing and tracking assessments. Features include test creation, result tracking, and performance analytics with file system storage.

A real-time fish species detection application using YOLO (You Only Look Once) computer vision model. Detects and identifies 13 different fish species with bounding boxes, confidence scores, and detailed species information including diet, lifespan, and estimated weight.