Graph Convolutional Network (GCN) Paper Explained

Big thanks to MakinaRocks for sponsoring this video, and I encourage you to check out Link which is a jupter lab extension they have developed to make notebooks more intuitive and easier to use. A few of the features I’ve found useful are: 1️⃣ Caching result from running cells in notebooks to avoid re-running them 2️⃣ Visualizing cell dependencies 3️⃣ Integrated version control Check it out⬇️ https://bit.ly/3F4COvv Link Demo Video 👉 https://youtu.be/uM2uPG-1eQQ Link Documentation 👉https://makinarocks.gitbook.io/link/ ❤️ Support the channel ❤️ https://www.youtube.com/channel/UCkzW5JSFwvKRjXABI-UTAkQ/join Paid Courses I recommend for learning (affiliate links, no extra cost for you): ⭐ Machine Learning Specialization https://bit.ly/3hjTBBt ⭐ Deep Learning Specialization https://bit.ly/3YcUkoI 📘 MLOps Specialization http://bit.ly/3wibaWy 📘 GAN Specialization https://bit.ly/3FmnZDl 📘 NLP Specialization http://bit.ly/3GXoQuP ✨ Free Resources that are great: NLP: https://web.stanford.edu/class/cs224n/ CV: http://cs231n.stanford.edu/ Deployment: https://fullstackdeeplearning.com/ FastAI: https://www.fast.ai/ 💻 My Deep Learning Setup and Recording Setup: https://www.amazon.com/shop/aladdinpersson GitHub Repository: https://github.com/aladdinpersson/Machine-Learning-Collection ✅ One-Time Donations: Paypal: https://bit.ly/3buoRYH ▶️ You Can Connect with me on: Twitter - https://twitter.com/aladdinpersson LinkedIn - https://www.linkedin.com/in/aladdin-persson-a95384153/ Github - https://github.com/aladdinpersson Timestamps: 0:00 - Introduction 1:00 - Sponsored Segment: Link 2:09 - Abstract and overview 4:13 - Introduction to the problem 8:53 - How GCNs work 13:47 - Theory of GCN derivation 21:25 - GCN Node classification example 24:33 - Conclusions & Results 25:13 - Ending thoughts #link #gcn