🔥🔥High-Performance Face Recognition Library on PaddlePaddle & PyTorch🔥🔥

A complete end-to-end demonstration in which we collect training data in Unity and use that data to train a deep neural network to predict the pose of a cube. This model is then deployed in a simulated robotic pick-and-place task.

An AI-driven solution for enhancing safety at construction sites. Utilises YOLOv8 for object detection to identify overhead hazards like heavy loads and steel pipes. Alerts are triggered if personnel are detected beneath these hazards. Dataset sourced from Taiwan's construction industry.

PyTorch model training and layer saturation monitor

Simplified Deep Image Matting training code with keras on tensorflow

Experiments with Model Training, Deployment & Monitoring

skrobot is a Python module for designing, running and tracking Machine Learning experiments / tasks. It is built on top of scikit-learn framework.

Implements an entire machine learning pipeline to train and evaluate a Random Forest Classifier on labeled gait data for walking. Data generated during the experiment has led to helpful insights in to the problem domain.

This is a capstone project associated with MLOps Zoomcamp. The end goal of the project is to build an end-to-end machine learning project containing feature engineering, training, validation, tracking, modeel deployment, hosting, and general engineering best practices aimed at making house price predictions.

Code for paper "Accelerating Federated Learning for IoT in Big Data Analytics with Pruning, Quantization and Selective Updating"

Deep Learning based research project for predicting mental state of a person.

Containerized Tensorflow-based image classification training utility with Streamlit-based interface designed to choose between common architectures and optimizers for quick hyperparameter tuning.

Demonstrates on how to train your model on custom class using tensorflow

Model training examples for NeoPulse AI Studio AMI

Predict next number in a sequence using a simple ANN. Modularized code with classes for data preparation, neural network architecture, and training.

Explore credit card approval prediction through data analysis and machine learning. Preprocess data, train logistic regression models, and optimize hyperparameters. Learn data preprocessing, feature engineering, model training, and evaluation. Dive into the world of machine learning with Python and popular libraries.

Run remote machine learning model training jobs right from the command line.

Evolutionary Neural Architecture Search framework that improves performance of your DL models

Easy-to-Use library to recognize faces, train the model, provide predictions

Neural networks training pipeline based on PyTorch