- Understanding the GitHub Flow
- Hello World
- Getting Started with GitHub Pages
- Git Handbook
- Forking Projects
- Be Social
- Making Your Code Citable
- Mastering Issues
- Mastering Markdown
- Documenting your projects on GitHub
This is the Graph Neural Networks: Hands-on Session from the Stanford 2019 Fall CS224W course.
In this tutorial, we will explore the implementation of graph neural networks and investigate what representations these networks learn. Along the way, we'll see how PyTorch Geometric and TensorBoardX can help us with constructing and training graph models.
Pytorch Geometric tutorial part starts at -- 0:33:30
Details on:
* Graph Convolutional Neural Networks (GCN)
* Custom Convolutional Model
* Message passing
* Aggregation functions
* Update
* Graph Pooling
In this tutorial I’ll explain how to build a simple working Recurrent Neural Network in TensorFlow. This is the first in a series of seven parts where various aspects and techniques of building…
Fullstack GraphQL Tutorial to go from zero to production covering all basics and advanced concepts. Includes tutorials for Apollo, Relay, React and NodeJS.
Going to a conference is always an excitement and fun: one can connect with like-minded individuals and exchange stimulating ideas. However, in order to make the most out of a conference, a lot of hard work is needed before, during and after the meeting. This blog post provides a checklist of things to do before,…
An attempt to create a convenient workspace that makes it possible to work with multiple custom python libraries, while keeping all benefits of Google Colaboratory.
An introduction to what a Mesh, Shader and Material is in Unity, how to set Shader Properties from C#, a brief look at Forward vs Deferred rendering and some information about Material instances and Batching. HLSL | Unity Shader Tutorials, @Cyanilux
Learn the Linux/ Unix command line (Bash) with our 13 part beginners tutorial. Clear descriptions, command outlines, examples, shortcuts and best practice.
Hi, I’m Greg, and for the last two years, I’ve been developing a 3d fractal exploration game, which started as just a “what if” experiment. I would describe myself as technical artist, meaning, I am…
Proteins play countless roles throughout the biological world, from catalyzing chemical reactions to building the structures of all living things. Despite this wide range of functions all proteins are made out of the same twenty amino acids, but combined in different ways. The way these twenty amino acids are arranged dictates the folding of the protein into its primary, secondary, tertiary, and quaternary structure. Since protein function is based on the ability to recognize and bind to specific molecules, having the correct shape is critical for proteins to do their jobs correctly. Learn more about the relationship between protein structure and function in this video.
Hi Guys, I have Always been asked to share my code which I use in my video. Answering people’s questions is great, and the feeling you get when you solve a p...
A collection of .BLEND and .FBX files to accompany the Robotic Design with Blender tutorial series on YouTube:(Part 1) https://youtu.be/aRBHMRa6pIA(Part 2) https://youtu.be/TKc-g84j2x8(Part 3) https://youtu.be/Cuo_ytkvCpo(Part
These tutorials walk you through writing medium-size software projects from scratch, step by step. The projects are based on real open-source software projects, and most of the tutorials stay true to the original source code. Every line of code is explained in detail, allowing you to thoroughly understand the project’s entire codebase.
List of 51 TensorFlow deep learning tutorial videos. TensorFlow™ is an open source software library for numerical computation using data flow graphs....
You remember prime numbers, right? Those numbers you can’t divide into other numbers, except when you divide them by themselves or 1? Right. Here is a 3000 year old question: Present an argument or…
- Aug. 31 – Sep. 4, 2020
- Csaba Szepesvari (University of Alberta, Google DeepMind; chair), Emma Brunskill (Stanford University), Sébastien Bubeck (MSR), Alan Malek (DeepMind), Sean Meyn (University of Florida), Ambuj Tewari (University of Michigan), Mengdi Wang (Princeton)
R. Sharipov. (2004)cite arxiv:math/0412421Comment: The textbook, AmSTeX, 132 pages, amsppt style, prepared for double side printing on letter size paper.
R. Sharipov. (2004)cite arxiv:math/0405323Comment: The textbook, AmSTeX, 143 pages, amsppt style, prepared for double side printing on letter size paper.
A. Slivkins. (2019)cite arxiv:1904.07272Comment: The manuscript is complete, but comments are very welcome! To be published with Foundations and Trends in Machine Learning.