In five courses, you are going learn the foundations of Deep Learning, understand how to build neural networks, and learn how to lead successful machine learning projects. You will learn about Convolutional networks, RNNs, LSTM, Adam, Dropout, BatchNorm, Xavier/He initialization, and more. You will work on case studies from healthcare, autonomous driving, sign language reading, music generation, and natural language processing. You will master not only the theory, but also see how it is applied in industry. You will practice all these ideas in Python and in TensorFlow, which we will teach.
In this post, I would like to share my practice with Facebook’s new Detectron2 package on macOS without GPU support for street view panoptic segmentation. If you want to create the following video by yourself, this post is all you need. This demo video clip is from my car’s dashcam footages from Preston, Melbourne. I used the PyTorch and Detectron2 to create this video with segmentation masks.
When I am using TensorFlow on my MacBook Air, I always get annoyed by the warnings comes from nowhere, so I followed the documentation below to build TensorFlow sources into a TensorFlow binary and installed it successfully. In theory, this will make the TF running faster on my machine.