🤗 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.

TensorFlow code and pre-trained models for BERT

The best ChatGPT that $100 can buy.

Best Practices on Recommendation Systems

🦉 Data Versioning and ML Experiments

Convert Machine Learning Code Between Frameworks

LLMs build upon Evol Insturct: WizardLM, WizardCoder, WizardMath

FastF1 is a python package for accessing and analyzing Formula 1 results, schedules, timing data and telemetry

An implementation of a deep learning recommendation model (DLRM)

Representation learning on large graphs using stochastic graph convolutions.

TensorFlow Reinforcement Learning

DeepWalk - Deep Learning for Graphs

TensorFlow Recommenders is a library for building recommender system models using TensorFlow.

NVTabular is a feature engineering and preprocessing library for tabular data designed to quickly and easily manipulate terabyte scale datasets used to train deep learning based recommender systems.

深度学习相关的模型训练、评估和预测相关代码

双色球+大乐透彩票AI预测

CTR prediction using FM FFM and DeepFM

SIGKDD'2019: DeepGBM: A Deep Learning Framework Distilled by GBDT for Online Prediction Tasks

Kaggle | Instacart Market Basket Analysis🥕🥉

XGBoost Feature Interactions Reshaped

Some deep learning based recsys for open learning.

2nd place solution🥕🥈

Train Word2vec Model based on Wikipedia

主流推荐系统Rank算法的实现

Tensorflow implementations of various Learning to Rank (LTR) algorithms.

Implementation of AutoInt: Automatic Feature Interaction Learning via Self-Attentive Neural Networks

Classical RecSys algorithms implemented by using TensorFlow Estimators