What you learn in the course
Introduction to Image Analysis: Basics, Perception, and Use Cases
Preprocessing Techniques: Labeling, Scaling, Filters, and Feature Detection
Training and Evaluation of Simple Convolutional Neural Networks (CNNs)
Overview of State-of-the-Art Models
Optimization and Hyperparameter Tuning
Use Case Anomaly Detection: Problem Definition, Labeling, Inference, Best Practices and Workflows
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