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Download Advanced Graph Neural Networks Course for Free

Download the complete Advanced Graph Neural Networks video course for free with high-definition MP4 video lectures, project exercise archives, and step-by-step masterclasses. Learn offline at your own pace with zero paywalls or recurring subscriptions.

27Lectures

1.7Total Hours

231.7MB Total Size

MP4 / 1080p HD

Instructor: Senior Industry Specialist

English

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Overview of graph neural networks

MP4 HD5m•10.49 MB

Stream

Prerequisites

MP4 HD1m•1.55 MB

Stream

Message passing in GNNs

MP4 HD3m•6.62 MB

Stream

Aggregation and transformation math

MP4 HD3m•7.15 MB

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Aggregation and transformation math in matrix form

MP4 HD3m•6.20 MB

Stream

Introducing graph attention

MP4 HD2m•5.47 MB

Stream

Computing the attention coefficient

MP4 HD3m•6.58 MB

Stream

Including attention in GNN layers

MP4 HD2m•4.61 MB

Stream

Getting set up with Colab and the PyTorch Geometric library

MP4 HD3m•5.95 MB

Stream

Exploring the Cora dataset

MP4 HD5m•12.09 MB

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Setting up the graph convolutional network

MP4 HD4m•9.67 MB

Stream

Training a graph convolutional network

MP4 HD6m•13.84 MB

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Node classification using a graph attention network

MP4 HD7m•15.09 MB

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Using the GATv2Conv layer for attention

MP4 HD4m•9.69 MB

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Understanding graph classification

MP4 HD5m•10.04 MB

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Exploring the PROTEINS Dataset for graph classification

MP4 HD4m•9.17 MB

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Minibatching graph data

MP4 HD3m•5.96 MB

Stream

Setting up a graph classification model

MP4 HD4m•9.84 MB

Stream

Training a GNN for graph classification

MP4 HD4m•8.81 MB

Stream

Eliminating neighborhood normalization and skip connections

MP4 HD3m•7.27 MB

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A quick overview of autoencoders

MP4 HD2m•5.23 MB

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Introducing graph autoencoders

MP4 HD2m•4.52 MB

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Splitting link prediction data

MP4 HD5m•12.08 MB

Stream

Understanding link splits

MP4 HD6m•13.76 MB

Stream

Designing an autoencoder for link prediction

MP4 HD6m•12.33 MB

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Training the autoencoder

MP4 HD7m•15.04 MB

Stream

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What You'll Master in this Free Download Course

Master practical concepts and hands-on skills in Other Professional Courses

Complete 27 video lectures with real-world examples and workflows

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About this Free Download Course

Advanced Graph Neural Networks, Explore graph neural networks (GNNs) in depth. Instructor Janani Ravi begins by delving into the workings of GNNs, covering message passing, aggregation, transformation, transformation math, and attention mechanisms like GATv2Conv. Janani explores practical applications such as node classification, graph classification, and link prediction using datasets like Cora and PROTEINS. Hands-on exercises on Colab with PyTorch Geometric provide experience in setting up and training GNN models. Learn about mini-batching and neighborhood normalization to tackle graph data challenges. This course is ideal for researchers, data scientists, and anyone interested in deep learning or graph theory. Tune in to unlock new potentials in data analysis and modeling with GNNs.

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