English | Size: 835 MB
Genre: eLearning
Graph neural network course from beginner to advanced.
What you’ll learn
Mastering the Basics of Graphs and Graph Neural Networks (GNNs)
Implementing GNN Models from Scratch
Apply GNNs to Real-World Scenarios like Recommendation Systems
Complete modern-day GNN problems and challenges
In this in-depth Udemy course on graph neural networks, you’ll embark on a journey to master the art of extracting valuable insights from graph data. Through a carefully crafted curriculum, you’ll first grasp the core principles of GNNs, understanding how they propagate information across nodes and edges to capture intricate relationships. With hands-on coding exercises, you’ll gain the confidence to implement GNN models from scratch. You’ll construct diverse architectures and witness the power of GNNs in action, including Graph Convolutional networks.
Graphs are ubiquitous in modern data analysis, from social networks to molecular structures, and GNNs are the cutting-edge tools to make sense of them. Through a carefully crafted curriculum, you’ll first grasp the core principles of GNNs, understanding how they propagate information across nodes and edges to capture intricate relationships.
This course is more than just theory and coding. You’ll learn to apply GNNs to real-world scenarios, solving problems like node classification and recommendation systems.
By the end of this course, you’ll possess the skills to transform raw graph data into actionable insights. Whether you’re a data scientist, machine learning practitioner, or curious learner, our Graph Neural Network course equips you with the tools to navigate the complex web of data all around us. Enroll now and unlock the potential of GNNs in your data analysis toolkit.
Who this course is for:
Data Science enthusiasts
Computer Science students
Machine Learning enthusiasts
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