In this video, the author explains the pipeline for training a neural network model using Convolutional Neural Networks (CNN) for landmark image classification. Those interested can follow the training pipeline and test the model on the author's Github.
This article recounts the author's struggle with overfitting in their first Convolutional Neural Network for image classification, where high training accuracy contrasted with poor validation results. It aims to explain how to identify and resolve overfitting, offering practical advice to avoid common frustrations.
This article details the author's personal journey in classifying clothing images using a Sequential Neural Network and the Fashion MNIST dataset, facing the challenge of differentiating sneakers from bags. After the model struggled with real-world photos, the author outlined strategies to overcome difficulties, including refining preprocessing and normalizing input, while also recognizing the need for CNNs for real-world data.