5 things to know before customizing your first machine learning model with MediaPipe Model Maker- Google Developers Blog

This post provides practical advice for developers customizing machine learning models using MediaPipe Model Maker. It details the importance of data preparation, simplifying model complexity, expecting multiple training iterations, prototyping outside the main application using MediaPipe Studio, and making incremental changes during the development cycle. It highlights the use of transfer learning with MediaPipe Model Maker, requiring less data than training from scratch, and suggests aiming for 100 examples per class. The post also mentions the use of Label Studio for data annotation and provides links to relevant Colab notebooks and documentation for image classification, gesture recognition, text classification, and object detection models.