• Regex
  • W3Schools: https://www.w3schools.com/python/python_regex.asp
  • DataCamp: https://app.datacamp.com/learn/courses/regular-expressions-in-python
• Web Scraping
  • Scrapy: https://youtu.be/s4jtkzHhLzY
    • Try to scrape bukabuku.com
  • Tweepy: https://youtu.be/zJYnn0FiPI4
  • BeautifulSoup:
    • https://towardsdatascience.com/step-by-step-tutorial-web-scraping-wikipedia-with-beautifulsoup-48d7f2dfa52d
    • https://youtu.be/ICXR9nDbudk
  • Google Playstore Review Scraper: https://youtu.be/-QUyD0YFYb0
  • PyGoogleNews: https://youtu.be/rQXL9A0ST5k
  • Selenium: youtube.com/watch?v=NLOEYFNYGvQ
• Text Processing:
  • Tokenization: https://youtu.be/FLZvOKSCkxY
  • Stopwords: https://youtu.be/w36-U-ccajM
  • Stemming: https://youtu.be/yGKTphqxR9Q
  • Lemmatization: https://youtu.be/uoHVztKY6S4
  • Chunking: https://youtu.be/JctmnczWg0U?t=953
  • Feature Extraction: https://github.com/algonacci/Natural_Language_Processing/blob/main/Text/11 - Text Preprocessing/C1_W1_lecture_nb_01_preprocessing.ipynb
  • Visualizing Word Frequencies: https://github.com/algonacci/Natural_Language_Processing/blob/main/12 - Word Frequencies/C1_W1_lecture_nb_02_word_frequencies.ipynb
• Vectorization:
  • CountVectorizer: https://kavita-ganesan.com/how-to-use-countvectorizer/#.YvpURHZBzIU
  • TF-IDF
  • Word2Vec
  • Tokenizer
    • Transformers Tokenizer: https://www.analyticsvidhya.com/blog/2021/09/a-deep-dive-into-transformers-library/?utm_source=linkedin&utm_medium=social&utm_campaign=new-article&utm_content=B&custom=LBI583
• Text Mining:
  • Tokenization: https://www.youtube.com/watch?v=fNxaJsNG3-s
  • Padding and Sequences: https://youtu.be/r9QjkdSJZ2g
  • Tokenization, Padding, and Sequences: https://github.com/algonacci/Natural_Language_Processing/blob/main/14 - Tokenization%2C Padding%2C Sequences%2C Embedding/TextProcessing_DeepLearning.ipynb
  • Word Embedding: https://www.tensorflow.org/text/guide/word_embeddings
  • Word2Vec: https://www.tensorflow.org/tutorials/text/word2vec
• Deep Learning:
  • GRU: https://pythonalgos.com/build-a-gru-rnn-in-keras/ https://towardsdatascience.com/illustrated-guide-to-lstms-and-gru-s-a-step-by-step-explanation-44e9eb85bf21
  • LSTM: https://www.tensorflow.org/text/tutorials/text_classification_rnn
  • BERT: https://www.tensorflow.org/text/tutorials/classify_text_with_bert
  • Transformers (BERT, GPT-3)
• Topic Classification:
  • Sentiment Analysis: https://youtu.be/Y_hzMnRXjhI
  • Text Emotions Classifier: https://huggingface.co/bergum/xtremedistil-l6-h384-go-emotion
  • Category
• Text Generation:
  • Bidirectional-LSTM: https://github.com/algonacci/Bangkit/blob/main/05 - Natural Language Processing/C3W4_Assignment.ipynb
• Token Classification
  • Named Entity Recognition:
    • https://youtu.be/LFXsG7fueyk
    • https://github.com/Lucaterre/spacyfishing
    • https://youtu.be/p_7hJvl7P2A
  • POS Tagging: https://youtu.be/6j6M2MtEqi8
• Question Answering System
  • BERT: https://github.com/algonacci/Question-Answering-BERT
  • HayStack: https://haystack.deepset.ai/overview/intro
• Text Summarization
  • Transformers Summarizer with Chunking: https://youtu.be/JctmnczWg0U
• Extractive QA
  • HayStack ExtractiveQAPipeline: https://docs.haystack.deepset.ai/docs/ready_made_pipelines
• Text Similarity:
  • Siamese Network:
    • https://youtu.be/6jfw8MuKwpI
    • https://youtu.be/4I3gS1cmqe4
• Machine Translation
  • Seq2Seq: https://towardsdatascience.com/machine-translation-with-the-seq2seq-model-different-approaches-f078081aaa37
• Information Retrieval
  • https://www.tutorialspoint.com/natural_language_processing/natural_language_processing_information_retrieval.htm
• Image Caption Generator
  • Image Captioning: https://www.tensorflow.org/tutorials/text/image_captioning
• Named Entity Disambiguation
  • Using Entity Relatedness: https://towardsdatascience.com/improving-named-entity-disambiguation-using-entity-relatedness-within-wikipedia-92f400ee5994

Great source

https://github.com/nlp-with-transformers/notebooks