<ul><li>This article discusses the author's experience in training and testing machine learning models for image classification.</li><li>The author used MobileNetV2, a pre-trained convolutional neural network optimized for speed and accuracy, and leveraged transfer learning to fine-tune the model for the specific dataset.</li><li>The author successfully evaluated the model's performance on unseen images and created an automated process to move classified images to their respective folders.</li><li>Future steps include improving model accuracy with a larger dataset, deploying the model in a real-world application, and integrating advanced ML techniques for better classification.</li></ul>

My Journey in Training and Testing Machine Learning Models for Image Classification

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