Learning Graph Neural Networks
Learning Graph Neural Networks
Duration: 2h 13m 12s | .MP4 1280x720, 30 fps(r) | AAC, 48000 Hz, 2ch | 226 MB
Genre: eLearning | Language: English
Duration: 2h 13m 12s | .MP4 1280x720, 30 fps(r) | AAC, 48000 Hz, 2ch | 226 MB
Genre: eLearning | Language: English
Graph neural networks—neural networks capable of working with graph data structures—apply deep learning to data structures to reveal fresh insights from their graphs. In this course, learn about the different use cases of graph modeling and how to train a graph neural network and evaluate its results. Instructor Janani Ravi starts with some background on graphs, including terminology and graph types. She then introduces graph machine learning concepts and the basics of graph neural networks. The last half of the course consists of exercises to help you set up and train graph neural networks using PyTorch Geometric, visualize graphs using NetworkX, and training a graph convolutional network for node labeling using the Cora dataset.
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