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Tags: JNUpython/DeepCTR

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v0.8.0

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v 0.8.0

- Support `Tensorflow Estimator` for large scale data and distributed training.  
- Support  different initializers for different embedding weights by settting `embeddings_initializer` of `SparseFeat`
- Support using pretrained weights to initialize embedding weights and frozen embedding weights. 
- Add new model `FwFM`
- API changes

v0.7.5

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v 0.7.5

- Fix numerical instability in `LayerNormalization`
- update `PNN` api

v0.7.4

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add flen

Add FLEN: Leveraging Field for Scalable CTR Prediction

v0.7.3

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Fix the inconsistency of prediction results when the model is loaded …

…with trained weights

v0.7.2

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fix some bugs (shenweichen#185)

- fix bug in `get_varlen_pooling_list`
- fix bug in `SequencePoolingLayer` when `mode='max'`
- Add alias `ONN` for model `NFFM`

v0.7.1

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v0.7.1

* Simplify `VarLenSparseFeat`, support setting weight_normalization.

* Fix problem of embedding size of `SparseFeat` in `linear_feature_columns`.

v0.7.0

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refactor feature columns

refactor feature columns 
- different features can use different `embedding_dim`
-  group-wise interaction is available by setting `group_name`

v0.6.3

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no message

v0.6.2

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simplify input logic

v0.6.1

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Update index.rst