[NeurIPS 2022] The official repository of Expression Learning with Identity Matching for Facial Expression Recognition

[TMLR] "Adversarial Feature Augmentation and Normalization for Visual Recognition", Tianlong Chen, Yu Cheng, Zhe Gan, Jianfeng Wang, Lijuan Wang, Zhangyang Wang, Jingjing Liu

Recognizing the Digits from 0-9 using their pixel values as attributes, using Deep Learning Model to Classify the Digits.

Solutions to Coursera's Intro to Machine Learning course in python

Evaluation of multiple graph neural network models—GCN, GAT, GraphSAGE, MPNN and DGI—for node classification on graph-structured data. Preprocessing includes feature normalization and adjacency-matrix regularization, and an ensemble of model predictions boosts performance. The best ensemble achieves 83.47% test accuracy.

CMU week 3 - whole process overview, data split, validation and model scoring

This is an example of Linear Regression done in SparkML and using the class PolynomialExpansion.

A Python implementation of the Iterative Feature Normalization algorithm