Welcome to DeepCTR’s documentation!¶
DeepCTR is a Easy-to-use , Modular and Extendible package of deep-learning based CTR models along with lots of core components layer which can be used to easily build custom models.You can use any complex model with model.fit()
and model.predict()
.
- Provide
tf.keras.Model
like interface for quick experiment. example - Provide
tensorflow estimator
interface for large scale data and distributed training. example - It is compatible with both
tf 1.x
andtf 2.x
.
Let’s Get Started! (Chinese Introduction)
You can read the latest code and related projects
- DeepCTR: https://github.com/shenweichen/DeepCTR
- DeepMatch: https://github.com/shenweichen/DeepMatch
- DeepCTR-Torch: https://github.com/shenweichen/DeepCTR-Torch
News¶
10/11/2020 : Refactor DNN
Layer. Changelog
09/12/2020 : Improve the reproducibility & fix some bugs. Changelog
06/27/2020 : Support Tensorflow Estimator
for large scale data and distributed training.Support different initializers for different embedding weights and loading pretrained embeddings.Add new model FwFM
. Changelog
DisscussionGroup 交流群¶
公众号:浅梦的学习笔记 wechat ID: deepctrbot
Cooperative promotion 合作推广¶
For more information about the recommendation system, such as feature engineering, user profile, matching, ranking and multi-objective optimization, online learning and real-time computing, and more cutting-edge technologies and practical projects :
更多关于推荐系统的内容,如 特征工程,用户画像,召回,排序和多目标优化,在线学习与实时计算以及更多前沿技术和实战项目 等可参考:
- Quick-Start
- Features
- Examples
- FAQ
- 1. Save or load weights/models
- 2. Set learning rate and use earlystopping
- 3. Get the attentional weights of feature interactions in AFM
- 4. How to extract the embedding vectors in deepfm?
- 5. How to add a long dense feature vector as a input to the model?
- 6. How to use pretrained weights to initialize embedding weights and frozen embedding weights?
- 7. How to run the demo with GPU ?
- 8. How to run the demo with multiple GPUs
- History