In this relatively short post, I’m going to show you how to deal with metrics and summaries in TensorFlow 2. Metrics, which can be used to monitor various important variables during the training of deep… Read More »Metrics and summaries in TensorFlow 2
It’s a great time to be practising deep learning. The main existing deep learning frameworks like TensorFlow, Keras and PyTorch are maturing and offer a lot of functionality to streamline the deep learning process. There are also other great tool sets emerging for the deep learning practitioner. One of these is the Google Colaboratory environment.… Read More »Google Colaboratory introduction – Learn how to build deep learning systems in Google Colaboratory
Deep learning can be complicated…and sometimes frustrating. Why is my lousy 10 layer conv-net only achieving 95% accuracy on MNIST!? We’ve all been there – something is wrong and it can be hard to figure out why. Often the best solution to a problem can be found by visualizing the issue. This is why TensorFlow’s… Read More »Introduction to TensorBoard and TensorFlow visualization