Kevin Weekly, CEO of Think Circuits, presents the “Introduction to DNN Training: Fundamentals, Process and Best Practices” tutorial at the May 2025 Embedded Vision Summit.
Training a model is a crucial step in machine learning, but it can be overwhelming for beginners. In this talk, Weekly provides a comprehensive introduction to the fundamentals of model training. He introduces the different types of training, such as supervised, unsupervised and semi-supervised learning, and then delves into techniques for supervised training.
He explains the training process, including error surfaces, optimization methods and back-propagation.
Weekly explains key concepts such as trainable parameters and data requirements. He also discusses the main “knobs” that control the training process, such as hyperparameters, regularization and batch normalization, and provides an overview of metrics to monitor during training, including loss curves, model accuracy and precision. Additionally, he covers common problems that arise during training, such as overfitting and underfitting, and introduces approaches to address these issues. Finally, he touches on popular training frameworks and provides resources for further learning.
See here for a PDF of the slides.
