python-text-mining-intro

Course's structure

1. Introduction
   1. Some definitions
   2. NLP use cases
   3. NLP challenges
   4. Python packages
2. Introduction to regular expressions
   1. Theory
   2. Examples
   3. Useful tools
   4. Exercises
3. Introduction to spaCy
   1. nlp object
   2. Documents, spans and tokens
   3. Lexical attributes
   4. Stemming
   5. Statistical models
   6. Lemmatization
   7. Sentence segmentation
   8. Part of speech tagging
   9. Syntactic dependencies
   10. Named entities recognition
   11. Stop words
   12. Exercises
4. Text vectorization
   1. Bag of words
   2. Tf-idf
   3. Word embeddings
5. Sentiment analysis modeling
   1. Sample submission
   2. Your turn!

Sources

• https://www.w3schools.com/python/python_regex.asp
• https://ieeexplore.ieee.org/document/8952499
• https://github.com/odenipinedo/Python/blob/master/datacamp/introduction%20to%20natural%20language%20processing%20in%20Python.ipynb
• https://course.spacy.io/en/chapter1
• https://stackabuse.com/python-for-nlp-tokenization-stemming-and-lemmatization-with-spacy-library/
• https://stackabuse.com/removing-stop-words-from-strings-in-python/
• https://openclassrooms.com/en/courses/6532301-introduction-to-natural-language-processing/6980811-apply-a-simple-bag-of-words-approach
• https://openclassrooms.com/en/courses/6532301-introduction-to-natural-language-processing/7067116-apply-the-tf-idf-vectorization-approach
• https://openclassrooms.com/en/courses/6532301-introduction-to-natural-language-processing/6980911-discover-the-power-of-word-embeddings
• https://www.shanelynn.ie/word-embeddings-in-python-with-spacy-and-gensim/
• https://ashutoshtripathi.com/2020/09/04/word2vec-and-semantic-similarity-using-spacy-nlp-spacy-series-part-7/
• https://israelg99.github.io/2017-03-23-Word2Vec-Explained/
• https://scionanalytics.com/text-mining-vs-natural-language-processing/#:~:text=NLP%20and%20text%20mining%20differ,than%20the%20meaning%20of%20content.
• https://www.folio3.ai/blog/why-natural-language-processing-is-important/#:~:text=By%20enabling%20machines%20to%20understand,%2C%20spell%20checks%2C%20and%20summarization.
• https://nexocode.com/blog/posts/definitive-guide-to-nlp/
• https://monkeylearn.com/blog/introduction-to-topic-modeling/#:~:text=Topic%20modeling%20is%20an%20unsupervised,characterize%20a%20set%20of%20documents.
• https://www.turing.com/kb/which-language-is-useful-for-nlp-and-why
• https://www.activestate.com/blog/natural-language-processing-nltk-vs-spacy/
• https://www.kaggle.com/code/lakshmi25npathi/sentiment-analysis-of-imdb-movie-reviews
• https://openclassrooms.com/en/courses/6532301-introduction-to-natural-language-processing/7047916-apply-classifier-models-for-sentiment-analysis