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nlp-course-projects

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Projects from students of NLP Course

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# nlp-course-projects
Projects from the students of Huawei NLP Course current run. Previous projects could be accessed [here](./prev).

|Name|Description|Team|Repository|
|----|-----------|----|----------|
|Building language model by users review about goods and using model in the context adversting|Creation of a word corpus from a website with goods' reviews. Teaching of the classification model based on these reviews. Context detection in the dialog and detection of a good's title in order to show ads according to the required context.|@akalend @rehcoeg|https://github.com/akalend/mobile_nlp_analisys|
|Movie Poster Caption Generation|Particular case of text generation task from images embeddings|@kazzand|https://github.com/kazzand/huaweiproject|
|A Russian Question Answering System for Inclusive Education|A closed domain model for question-answering in Russian built with transfer learning techniques. The model is fine-tuned on a custom dataset collected with the methodology described in the SQuAD original paper|@vifirsanova|https://github.com/vifirsanova/nlp-huawei-project|
|Indonesian-Russian Machine Translation|Indonesian-Russian translation pair is pretty weak now even in Yandex and Google translation systems. I try to find extend knowing ind-ru corpuses by mapping ind-en and en-rus corpuses. The main goal of this project is to practice with models based on Transformers and build the machine translation system producing the decent BLEU.|@minakyan|https://github.com/minakovaa/indonesian-russian-translation|
|Sentiment Analysis and AutoML|The goal is to perform the Sentiment Analysis on the amazon-fine-food-reviews and compare different hyperparameters search engines: hyperopt, BOHB and Optuna |@aazarov|https://github.com/aazarov/NLP_SentimentAnalysis_HyperparametersSearch|
|English sentiment analysis|I will try to solve common NLP problem related to sentiment analysis. The data is taken from Twitter and needs to be pre-processed, bacause the texts are very raw. Also, since the classes are unbalanced, I will try to apply data augmentation.|@slavkostrov|https://github.com/slavkostrov/project-sentiment-eng|
|Topic modeling and classification news on Hebrew| The goal is gathering data and creating a classification model on Hebrew, which is one of the low-resource languages such, and also performing topic modeling|@imvladikon|https://github.com/imvladikon/huawei-nlpcourse-project|
|Russian Text Sentiment Transfer|Transforming a sentence to alter its sentiment while preserving the content|@orzhan|https://github.com/orzhan/russian-text-sentiment-transfer|
|Domain adaptation of transformer model for improving semantic search|I am exploring the domain adaptation of the transformer model for improving search relevancy.|@algis|https://github.com/Dumbris/semantic-search-domain-adaptation|
|Predicting user ratings by movie's description|The task of predicting a number from the text is classical, but the found solution for data from the TMDB website on a similar dataset are based not only on the description, and have also large number of other fields. In this task we will try using only description to get a similar result or better|@aakzn|https://gitlab.com/iKzN/predict-film-rating-votes-by-overview|
|Topical extractive summarization|Topical extractive summarization is directed toward extract sentences most relevant to a given topic.|@pacifikus|https://github.com/pacifikus/nlp-course|

nlp-course-projects

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