pytorch-lr-scheduler

Recommendation Algorithm大规模推荐算法库，包含推荐系统经典及最新算法LR、Wide&Deep、DSSM、TDM、MIND、Word2Vec、Bert4Rec、DeepWalk、SSR、AITM，DSIN，SIGN，IPREC、GRU4Rec、Youtube_dnn、NCF、GNN、FM、FFM、DeepFM、DCN、DIN、DIEN、DLRM、MMOE、PLE、ESMM、ESCMM, MAML、xDeepFM、DeepFEFM、NFM、AFM、RALM、DMR、GateNet、NAML、DIFM、Deep Crossing、PNN、BST、AutoInt、FGCNN、FLEN、Fibinet、ListWise、DeepRec、ENSFM，TiSAS，AutoFIS等，包含经典推荐系统数据集criteo 、movielens等

A learning rate range test implementation in PyTorch

Play deep learning with CIFAR datasets

Visualize Tensorflow's optimizers.

numpy 实现的 周志华《机器学习》书中的算法及其他一些传统机器学习算法

Improving MMD-GAN training with repulsive loss function

A method for assigning separate learning rate schedulers to different parameters group in a model.

This repository focuses on the Neural Networks and deep learning. It is a workbook you can refer it for a reference. I'll Include following content here: Neurons, perceptrons, weight and biases, learning rate, activation form, hyper parameters, RNN, CNN and other popular concepts.

Analyze the performance of 7 optimizers by varying their learning rates

Neural net solver with auto-tuned hyperparameters (Python 3.5)