{"version":"1.0","type":"rich","title":"Gist 98636bb57280e38492740cdbe9c4901c","description":"This example demonstrates a deep learning workflow for classifying brain images using TensorFlow and Keras. It loads CSV data from the braindr dataset, displaying a pandas DataFrame with vote counts, rater identities, and mean ratings for each image. The code builds a convolutional neural network with layers like Conv2D, MaxPooling2D, Dropout, and LeakyReLU, using Keras' Sequential API. It configures the model for GPU execution, imports optimizers such as RMSprop and Adam, and prepares callbacks like ModelCheckpoint for training.","provider_name":"VizHub AI Studio","provider_url":"https://next.vizhub.com","html":"<iframe src=\"https://next.vizhub.com/viz/gist-98636bb57280e38492740cdbe9c4901c?mode=embed\" width=\"960\" height=\"500\" scrolling=\"no\" frameborder=\"1\"></iframe>","width":960,"height":500,"cache_age":3600}