anthonysong98 Goto Github PK

2048-game

Final Project for the course

advml2020

Advanced Topics in Statistical Machine Learning, Oxford Statistics, Hilary Term 2020

ai-project-for-gomoku

Record my progress on my first AI project for Gomoku (codes will be released at the end of this semester)

algorithm

algorithms

Algorithms, 4th edition textbook, implemented by java

autogl

An autoML framework & toolkit for machine learning on graphs.

awesome-graph-based-semi-supervised-learning

A collection of resources for graph-based semi-supervised learning (GSSL).

awesome-random-forest

Random Forest - a curated list of resources regarding random forest

benchmarking-gnns

Repository for benchmarking graph neural networks

best_ai_paper_2020

A curated list of the latest breakthroughs in AI by release date with a clear video explanation, link to a more in-depth article, and code

books

some useful Books (updating from time to time)

brain-tokyo-workshop

🧠🗼

clrs

:notebook:Solutions to Introduction to Algorithms

cosmos

Algorithms that run our universe | Your personal library of every algorithm and data structure code that you will ever encounter | Ask us anything at our forum

cs229-machine-learning-stanford-fall-2016

CS229 Machine Learning Class.

cs231n

cuda-samples

Samples for CUDA Developers which demonstrates features in CUDA Toolkit

cuda_scheduling_examiner_mirror

A public mirror of an internally-maintained tool for examining GPU scheduling behavior.

deepfool

A simple and accurate method to fool deep neural networks

deepsnap

Python library assists deep learning on graphs

deepwalk

DeepWalk - Deep Learning for Graphs

dgl

Python package built to ease deep learning on graph, on top of existing DL frameworks.

documentation

Official documentation for the Raspberry Pi

drone

SRTP project for drone

e2e

ebook

classic books of computer science

exercise

exercise for nndl

gan-for-tabular-data

We well know GANs for success in the realistic image generation. However, they can be applied in tabular data generation. We will review and examine some recent papers about tabular GANs in action.

graph-ai-deadlines

:alarm_clock: Graph AI conference deadline countdowns

graph-based-deep-learning-literature

links to conference publications in graph-based deep learning