How-To Geek on MSN

Generate realistic test data in Python fast. No dataset required

Learn the NumPy trick for generating synthetic data that actually behaves like real data.
IEEE

A Comparative Study of CNN-Based Predictive Maintenance Techniques on C-MAPSS Dataset

Abstract: In this study, convolutional neural network (CNNs) based predictive maintenance ($\mathbf{P d M}$) techniques are performed on the well-known jet engine data called the Commercial Modular ...
Circuit Digest

ESP32-CAM Currency Recognition System using Edge Impulse

TinyML / Edge AI, ESP32-CAM camera interfacing, Edge Impulse workflow, Image classification & object detection on ...
IEEE

Comparison of K-Means Algorithms and Fuzzy C-Means Algorithms for Clustering Customers Dataset

Abstract: Processing customer data results in the ability to predict the facts of the business environment. Data helps operate the business optimally, namely by developing market share, increasing ...
GitHub

AAAI-23 Lab for Innovative Uses of Synthetic Data

Welcome to the AAAI-23 Lab for Innovative Uses of Synthetic Data! In this repository you will find materials required to complete the Lab. The Lab will start on Wednesday, 8 February 2023, 14:00 EST.