در حال حاضر محصولی در سبد خرید شما وجود ندارد.
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.
در این روش نیاز به افزودن محصول به سبد خرید و تکمیل اطلاعات نیست و شما پس از وارد کردن ایمیل خود و طی کردن مراحل پرداخت لینک های دریافت محصولات را در ایمیل خود دریافت خواهید کرد.
Combining and Shaping Data
Implementing Bootstrap Methods in R
آموزش حل مشکلات پیچیدگی داده ها
Representing, Processing, and Preparing Data
Advanced Graph Neural Networks
Learning H20.ai
Scala 2 Methods and Functions
Building Your First scikit-learn Solution
Building Machine Learning Models on Databricks
Image Classification with PyTorch
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