Deep Learning Dynamics: CNN Model for Brain Tumour Detection

The post describes a project that utilizes convolutional neural networks (CNNs) to classify brain tumours from MRI images. The project uses a dataset of 15,000 images and employs various data augmentation and pre-processing techniques. The CNN model achieves 96% accuracy in classifying gliomas, meningiomas, and pituitary tumours. The process includes detailed data preparation, model architecture design, and performance evaluation, addressing challenges like class imbalance and overfitting. Future improvements include expanding the dataset and refining the model architecture for better diagnostic support.