AISaturdaysLagos / edge-computing
The workshop is designed to foster an enabling environment for individuals to build competence in the Edge Computing space.
☆14Updated last year
Related projects: ⓘ
- The following is a machine learning project to classify induction motor fault modes.☆32Updated 2 years ago
- This project is about predictive maintenance with machine learning. It's a final project of my Computer Science AP degree.☆45Updated last year
- In this repository you will find TinyML course syllabi, assignments/labs, code walkthroughs, links to student projects, and lecture video…☆148Updated 2 years ago
- Hands-On Artificial Intelligence for IoT, published by Packt☆123Updated last year
- Time-series modeling project that predicts the future number of electric vehicles in Washington state counties to identify locations with…☆15Updated 3 years ago
- Learning Pytorch☆13Updated 10 months ago
- ☆30Updated 3 weeks ago
- This repository holds the Google Colabs for the EdX TinyML Specialization☆108Updated 7 months ago
- Digital twin with Python☆33Updated 2 years ago
- ☆11Updated 3 years ago
- time-series prediction for predictive maintenance☆47Updated 5 years ago
- Deep Learning applied to predictive maintenance use cases☆32Updated 4 years ago
- Machine learning to predict time domain sensor data. Onsite data, live predict, on site training☆18Updated last year
- This repository shows how to deploy machine learning models on Azure IoT Edge.☆22Updated 3 years ago
- SensiML's open-source AutoML solution for Edge AI model development☆41Updated last week
- TinyML example showing how to do anomaly detection with Python and Arduino☆129Updated 3 years ago
- Student Materials for MTC Azure ML Workshop☆30Updated 7 years ago
- Predictive Maintenance System for Digital Factory Automation☆42Updated 5 years ago
- Illustrating a typical Predictive Maintenance use case in an Industrial IoT Scenario. By using Statistical Modelling and Data Visualizati…☆19Updated 2 years ago
- ☆182Updated 2 months ago
- Predicting the Remaining Useful Life (RUL) of simulated Turbofan Engines using Spark ML, Spark Structured Streaming, and Kafka.☆20Updated last year
- Dashboard designed to demonstrate the power of Machine Learning to predict failures (Remaining Useful Life (RUL)) in wind turbines. To pr…☆37Updated 2 years ago
- ☆17Updated 5 months ago
- Dash web app showing when an engine is expected to fail powered by vaex and tf/keras.☆15Updated 3 years ago
- This workshop will familiarize you with some of the key steps towards building an end-to-end predictive maintenance system leveraging Ama…☆28Updated 4 years ago
- This research project will illustrate the use of machine learning and deep learning for predictive analysis in industry 4.0.☆118Updated 3 years ago
- This repo demonstrates how to build a surrogate (proxy) model by multivariate regressing building energy consumption data (univariate and…☆22Updated last year
- Deep Learning and XAI Techniques for Anomaly Detection, published by Packt☆35Updated last year
- ☆11Updated 2 years ago
- Anomaly detection in industrial IoT sensors (Collecting data for predictive maintenance)☆11Updated 4 years ago