Defining a network structure

The hardest part if to develop an intuition to decide on what layers you will include in a given network since the network will perform different depending on the complexity of the task, some recommended things to try are: Change the number of convolutional layers Increase the size of convolutional kernels for larger images Change…

Data augmentation

In order to improve models without adding new data, we can do data augmentation, this will work well for images that do make sense to make transformations on top of, so for example it is not a good idea to do it for text or numbers because text the orientation of characters in these cases…

100DaysOfMLCode Index

  100DaysOfMLCode Index Attention mechanisms Batch size CNNs Computer Vision Conda Data Augmentation Defining a network structure Downloading Datasets Dropout Embeddings FastAI Filtered Images Facia-Keypoints-Detector notes GPU States High bias & high variance Hyperparameters Image Captioning Project Notes Intro to Pandas Lab Jobs in Computer Vision Layer Shapes Learning Rates Localization LSTM cells Momentum Machine…

GPU

The GPU performance state APIs are used to get and set various performance levels on a per-GPU basis. P-States are GPU active/executing performance capability and power consumption states. P-States range from P0 to P15, with P0 being the highest performance/power state, and P15 being the lowest performance/power state. Each P-State maps to a performance level.…