DidaWiki

Strumenti Utente

Strumenti Sito

Ti trovi qui: DidaWiki » mds » Text Analytics (635AA) A.Y. 2023/24
mds:txa:start

Differenze

Queste sono le differenze tra la revisione selezionata e la versione attuale della pagina.

Link a questa pagina di confronto

Entrambe le parti precedenti la revisione Revisione precedente
Prossima revisione 		Revisione precedente
Prossima revisione Entrambe le parti successive la revisione
mds:txa:start [30/09/2021 alle 14:15 (3 anni fa)]
Andrea Esuli [Lecture Notes] 		mds:txa:start [04/04/2022 alle 10:19 (2 anni fa)]
Andrea Esuli [Exam]
Linea 46: Linea 46:
 The purpose of the project is to let you have some hands on experience on applying the concepts and methods seen during the course to practical text analytics problems. The purpose of the project is to let you have some hands on experience on applying the concepts and methods seen during the course to practical text analytics problems.
  
-Projects may be based on challenges proposed in either research forums ([[https://alt.qcri.org/semeval2020/|Semeval]], [[http://www.evalita.it/|Evalita]]) or other platforms ([[https://kaggle.com|Kaggle]]). Students are also invited to propose a project on problem based on other sources (e.g., recent papers on ArXiv [[https://arxiv.org/list/cs.CL/new|CL]] or [[https://arxiv.org/list/cs.AI/new|AI]]), or their own interests.+Projects may be based on challenges proposed in either research forums ([[https://alt.qcri.org/semeval2020/|Semeval]], [[http://www.evalita.it/|Evalita]]) or other platforms ([[https://kaggle.com|Kaggle]]). Students are also invited to propose a project based on other sources (e.g., recent papers on ArXiv [[https://arxiv.org/list/cs.CL/new|CL]] or [[https://arxiv.org/list/cs.AI/new|AI]]), or their own interests.
  
 Students may work solo or in groups up to three persons. Students may work solo or in groups up to three persons.
Linea 58: Linea 58:
 | 2021/09/24 | Introduction to python 1/2 | {{ :mds:txa:03_-_introduction_to_python.pdf |}} {{ :mds:txa:03_1_introduction_to_python.zip |}}|  | 2021/09/24 | Introduction to python 1/2 | {{ :mds:txa:03_-_introduction_to_python.pdf |}} {{ :mds:txa:03_1_introduction_to_python.zip |}}| 
 | 2021/09/27 | Introduction to python 2/2 |  |  | 2021/09/27 | Introduction to python 2/2 |  | 
-| 2021/10/01 | Probabilistic Language Models | {{ :mds:txa:04_-_probabilistic_language_models.pdf |}} {{ :mds:txa:04_1_probabilisticlanguagemodel.zip |}}|  +| 2021/10/01 | Probabilistic Language Models 1/2 | {{ :mds:txa:04_-_probabilistic_language_models.pdf |}} {{ :mds:txa:04_1_probabilisticlanguagemodel.zip |}}|  
-| 2021/10/04 |  |  | +| 2021/10/04 | Probabilistic Language Models 2/2 |  | 
-| 2021/10/08 |  |  | +| 2021/10/08 | Text Indexing: Regular expressions | {{ :mds:txa:05_-_text_indexing.pdf |}} {{ :mds:txa:05_1_strings_regular_expressions_and_bs4.zip |}}  | 
-| 2021/10/11 |  |  | +| 2021/10/11 | Text Indexing: NLTK, Collocations | {{ :mds:txa:05_2_nltk.zip |}} {{ :mds:txa:05_3_collocations.zip |}} | 
-| 2021/10/15 |  |  | +| 2021/10/15 | Text Indexing: Spacy, Feature selection, Pipeline | {{ :mds:txa:05_4_spacy_text_processing.zip |}}  | 
-| 2021/10/18 |  |  | +| 2021/10/18 | Text Indexing: Notebook. Introduction to Machine Learning | {{ :mds:txa:05_5_text_indexing_sklearn.zip |}} {{ :mds:txa:06_-_machine_learning_for_text_analytics.pdf |}}| 
-| 2021/10/22 |  |  | +| 2021/10/22 | Machine Learning for TA: Paradigms and models |  {{ :mds:txa:06_-_machine_learning_for_text_analytics.pdf |}} | 
-| 2021/10/25 |  |  | +| 2021/10/25 | Machine Learning for TA: the complete pipeline | {{ :mds:txa:06_1_classification_sklearn.zip |}} | 
-| 2021/10/29 |  |  | +| 2021/10/29 | Machine Learning for TA: Feature engineering, Topic Modeling | {{ :mds:txa:06_2_classification_feature_engineering.zip |}} {{ :mds:txa:06.3_-_topic_modeling.pdf |}} {{ :mds:txa:06.4_-_topic_modeling.ipynb.zip |}} | 
-| 2022/11/05 |  |  | +| 2022/11/05 | Experimental protocols and optimization | {{ :mds:txa:07_-_experiments.pdf |}} {{ :mds:txa:07_1_optimization_sklearn.zip |}} | 
-| 2022/11/08 |  |  | +| 2022/11/08 | Information Extraction, Entity Annotation | {{ :mds:txa:08_-_information_extraction.pdf |}} {{ :mds:txa:08_1_spacy_ner_train.zip |}}| 
-| 2022/11/12 |  |  | +| 2022/11/12 | Data collection | {{ :mds:txa:09_-_data_collection.pdf |}} {{ :mds:txa:09_1_scraping.zip |}} {{ :mds:txa:09_2_data_from_twitter.zip |}}| 
-| 2022/11/15 |  |  | +| 2022/11/15 | Introduction to Neural Networks | {{ :mds:txa:10_-_a_primer_on_neural_networks.pdf |}} {{ :mds:txa:10.1_-_example_of_backpropagation.pdf |}} {{ :mds:txa:10.2_-_svm_to_nn.ipynb.zip |}}| 
-| 2022/11/19 |  |  | +| 2022/11/19 | Text classification with Neural Networks | {{ :mds:txa:10.3_-_classification_-_cnnnet.ipynb.zip |}} {{ :mds:txa:10.4_-_classification_-_lstmnet.ipynb.zip |}} {{ :mds:txa:10_5_textgeneration.zip |}}| 
-| 2022/11/22 |  |  | +| 2022/11/22 | Neural Language Models, Word2Vec | {{ :mds:txa:11_-_neural_language_models.pdf |}} {{ :mds:txa:11_1_wordembeddings.zip |}} | 
-| 2022/11/26 |  |  | +| 2022/11/26 | Doc2Vec, Transformer, BERT  | {{ :mds:txa:11_2_documentembeddings.zip |}} {{ :mds:txa:11_3_bert_finetune_binary.zip |}} {{ :mds:txa:11_4_bert_finetune_multiclass.zip |}}| 
-| 2022/11/29 |  |  | +| 2022/11/29 | SimpleTransformers | {{ :mds:txa:11_5_simpletransformers_finetune_binary.zip |}} {{ :mds:txa:11_6_simpletransformer_generation_and_representation.zip |}} | 
-| 2022/12/03 |  |  |+| 2022/12/03 | Sentiment Analysis | {{ :mds:txa:12_-_sentiment_analysis.pdf |}} {{ :mds:txa:12_1_vader.zip |}}|
  
 ==== Textbooks ==== ==== Textbooks ====
mds/txa/start.txt · Ultima modifica: 15/01/2024 alle 10:31 (3 mesi fa) da Laura Pollacci

Strumenti Pagina

Donate Powered by PHP Valid HTML5 Valid CSS Driven by DokuWiki