Spark-nlp

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Overview
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* We are very excited to release the very first multi-class text classifier in Spark NLP v2.4.4! We have built a generic ClassifierDL annotator that uses the state-of-the-art Universal Sentence Encoder as an input for text classifications. The ClassifierDL annotator uses a deep learning model (DNNs) we have built inside TensorFlow and supports up to 50 classes.
* We are also happy to announce the support of yet another language: Russian! We have trained and prepared 5 pre-trained models and 6 pre-trained pipelines in Russian.

**NOTE**: ClassifierDL is an experimental feature in 2.4.4 release. We have worked hard to aim for simplicity and we are looking forward to your feedback as always.

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New Features
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* Introducing an experimental multi-class text classification by using the DNNs model in TensorFlow called `ClassifierDL`. This annotator can train any dataset from 2 up to 50 classes.
* 5 new pretrained Russian models (Lemma, POS, 3x NER)
* 6 new pretrained Russian pipelines

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Enhancements
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* Add param to NerConverter to override modified tokens instead of original tokens

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Bugfixes
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* Fix TokenAssembler
* Fix NerConverter exception when NerDL is trained with different tagging style than IOB/IOB2

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Overview
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This minor release fixes a bug on our Python side that was introduced in 2.4.2 release.
As always, we thank our community for their feedback and questions in our Slack channel.

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Bugfixes
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* Fix Python imports which resulted in AttributeError: module 'sparknlp' has no attribute


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Overview
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This minor release fixes a few bugs in some of our annotators reported by our community.
As always, we thank our community for their feedback and questions in our Slack channel.

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Bugfixes
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* Fix UniversalSentenceEncoder.pretrained() that failed in Python
* Fix ElmoEmbeddings.pretrained() that failed in Python
* Fix ElmoEmbeddings poolingLayer param to be a string as expected
* Fix ChunkEmbeddings to preserve chunk's index
* Fix NGramGenerator and missing chunk metadata

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New Features
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* Add GPU support param in Spark NLP start function: sparknlp.start(gpu=true)
* Improve create_model.py to create custom TF graph for NerDLApproach

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Documentation
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* Update documentation for release of Spark NLP 2.4.x
* Update the entire [spark-nlp-workshop](https://github.com/JohnSnowLabs/spark-nlp-models) notebooks for Spark NLP 2.4.x
* Update the entire [spark-nlp-models](https://github.com/JohnSnowLabs/spark-nlp-workshop) repository with new pre-trained models and pipelines

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Overview
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This minor release fixes a few bugs in some of our annotators reported by our community.
As always, we thank our community for their feedback and questions in our Slack channel.

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Bugfixes
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* Improve ChunkEmbeddings annotator and fix the empty chunk result
* Fix UniversalSentenceEncoder crashing on empty Tensor
* Fix NorvigSweetingModel missing sentenceId that results in NGramsGenerator crashing
* Fix missing storageRef in embeddings' column for ElmoEmbeddings annotator

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Documentation
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* Update documentation for release of Spark NLP 2.4.x
* Add new features such as ElmoEmbeddings and UniversalSentenceEncoder
* Add multiple programming languages for demos and examples
* Update the entire [spark-nlp-models](https://github.com/JohnSnowLabs/spark-nlp-models) repository with new pre-trained models and pipelines

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Bugfixes
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* https://github.com/JohnSnowLabs/spark-nlp/pull/702 Date matcher fixes flexible dates
* https://github.com/JohnSnowLabs/spark-nlp/pull/718 Fixed a bug in a pragmatic sentence detector where a sub matched group contained a dollar sign.
* https://github.com/JohnSnowLabs/spark-nlp/pull/719 Move import to top-level to avoid import fail in Spark NLP functions
* https://github.com/JohnSnowLabs/spark-nlp/pull/709 https://github.com/JohnSnowLabs/spark-nlp/pull/716 Some improvements in our documentation thanks to marcinic howmuchcomputer

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Overview
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This minor release fixes a bug in ChunkEmbeddings causing an out of boundaries exception in some scenarios. We
also switch to maven coordinates as default source for start() function since spark-packages has not been responsive
on their package approval process. Thank you all for your consistent feedback.

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Bugfixes
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* Fixed a bug in Chunk Embeddings caused by out of bound exception in some scenarios

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Other
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* start() function switched to use maven coordinates instead

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