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Production-ready platform for agentic workflow development.
🤗 Transformers: the model-definition framework for state-of-the-art machine learning models in text, vision, audio, and multimodal models, for both inference and training.
NeurIPS'18: Co-teaching: Robust Training of Deep Neural Networks with Extremely Noisy Labels
Keras/Pytorch implementation of N-BEATS: Neural basis expansion analysis for interpretable time series forecasting.
Google Research
A Python package to assess and improve fairness of machine learning models.
A tutorial demonstrating how to implement deep learning models for time series forecasting
Python library for converting Scikit-Learn pipelines to PMML
Pytorch implementations of Bayes By Backprop, MC Dropout, SGLD, the Local Reparametrization Trick, KF-Laplace, SG-HMC and more
Source code for AAAI2019 paper "Cash-out User Detection based on Attributed Heterogeneous Information Network with a Hierarchical Attention Mechanism"
Kaggle | Web Traffic Forecasting 📈
A TensorFlow implementation of DeepMind's WaveNet paper
This repo aims to be a useful collection of notebooks/code for understanding and implementing seq2seq neural networks for time series forecasting. Networks are constructed with keras/tensorflow.
📃 𝖀𝖓𝖔𝖋𝖋𝖎𝖈𝖎𝖆𝖑 PyTorch Implementation of DA-RNN (arXiv:1704.02971)
Framework for building complex recurrent neural networks with Keras
A deep matching model library for recommendations & advertising. It's easy to train models and to export representation vectors which can be used for ANN search.
An Industrial Graph Neural Network Framework
An elegant PyTorch deep reinforcement learning library.
Jittor is a high-performance deep learning framework based on JIT compiling and meta-operators.
An implementation of the focal loss to be used with LightGBM for binary and multi-class classification problems
Tool for producing high quality forecasts for time series data that has multiple seasonality with linear or non-linear growth.