LIU Zhengying

autodl_starting_kit_stable. Starting kit for AutoCV/AutoDL challenge (https://autodl.chalearn.org)

autodl. A machine learning competition in Automated Deep Learning (AutoDL), co-organized by ChaLearn, Google and 4Paradigm. Accepted at NeurIPS 2019.

autodl-contrib. Join us and be credited for AutoDL challenge - the next big thing in automated machine learning. Organized by Google, ChaLearn and 4Paradigm.

info232. This GitHub repository aims to share teaching resources for L2 students enrolled in the course INFO232 (mini-projet) at Université Paris Sud / Paris-Saclay.

automl-workflow. An attempt for a universal AutoML workflow API design. Featured AutoDL challenge winning teams DeepWisdom and DeepBlueAI.

email-recipient-recommendation. The data challenge for the course "Advanced Machine Learning for Graph and Text" in the Master Data Science program of Université Paris-Saclay.

Kernel-Methods-Data-Challenge. The data challenge for the course Kernel Methods for Machine Learning of the MVA program

kimina. A Lean tactic that invokes the Kimina Prover Preview model to offer proof suggestions.

rl-aic. A course I followed during my PhD on Reinforcement Learning in the AIC master program.

axa-data-challenge-yellow. Project for the 2016 Data Challenge of Master Data Science of Paris-Saclay.