جمع جزء: 139,000 تومان
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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.
یادگیری ماشینی برای خدمات مالی
Introduction to Attention-Based Neural Networks
Understanding Statistical Models and Mathematical Models
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آموزش ساخت مدل های رگرسیون بوسیله scikit-learn
آموزش Scrape صفحات وب به زبان Python
Building Statistical Summaries with R
AI Workshop: Build a Neural Network with PyTorch Lightning
Expediting Deep Learning with Transfer Learning: PyTorch Playbook
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