Here are a selection of projects that I have worked on over the years.
This setup provides a basic integration of SHAP into your model training process, enabling you to gain insights into how different features affect the model’s predictions. You can further customize and extend the XAI component based on your specific needs and requirements.
About This code continuously reads data from multiple sensors, processes it to calculate orientation (roll, pitch, yaw) and other environmental parameters (pressure, temperature, humidity, proximity), and transmits this data to another device using Serial1. It uses the Madgwick filter for sensor fusion and applies error corrections to the sensor readings.
The provided code is written in Embedded C and is designed for an AVR microcontroller (likely ATmega128A), focusing on implementing a BCH (31,16) error-correcting code for encoding and decoding messages. It also includes UART communication for data transmission and uses timers for timing operations.
This code is a script for training an image classification model MobileNet using PyTorch. The code is structured to facilitate easy training, evaluation, and monitoring of a deep learning model for image classification.
Fundamental files to train and evaluate a simple LSTM model which can be trained on a time-series dataset composed of two input features and two outputs classes.
