PyTorch Essential Training: Deep Learning
PyTorch Essential Training: Deep Learning
.MP4, AVC, 1280x720, 30 fps | English, AAC, 2 Ch | 56m | 128 MB
Instructor: Jonathan Fernandes
.MP4, AVC, 1280x720, 30 fps | English, AAC, 2 Ch | 56m | 128 MB
Instructor: Jonathan Fernandes
PyTorch is quickly becoming one of the most popular deep learning frameworks around, as well as a must-have skill in your artificial intelligence tool kit. It's gained admiration from industry leaders due to its deep integration with Python; its integration with top cloud platforms, including Amazon SageMaker and Google Cloud Platform; and its computational graphs that can be defined on the fly. In this course, join Jonathan Fernandes as he dives into the basics of deep learning using PyTorch. Starting with a working image recognition model, he shows how the different components fit and work in tandem—from tensors, loss functions, and autograd all the way to troubleshooting a PyTorch network.
Topics include:
Training a network
Making predictions
Working with classes and tensors
Working with loss, autograd, and optimizers
Troubleshooting a PyTorch network
CPU/GPU usage
PyTorch Essential Training: Deep Learning
