- Announcements!
- Video overview & timeline
- Bag of words (BOW) overview
- Bag of words example code! (sklearn | CountVectorizer, fit_transform)
- Building a text classification model using bag-of-words (SVM)
keith enum 😂👌
- Predicting new utterances classes using our model (transform)
If anyone else is getting "CLOTHING" here, try creating your vectorizer like this:vectorizer = CountVectorizer(stop_words=["the"])
- Unigram, bigram, ngrams (using consecutive words in your model)
- Word vectors overview
- Word vectors example code! (Using spaCy library)
- Building a text classification model using word vectors
- Predicting new utterances using our model
"I went to the bank and wrote a check" is an incorrect English sentence.It should have been "I went to the bank and wrote a cheque"
- Regexes (pattern matching) in Python.
- Stemming/Lemmatization in Python (text normalization w/ NLTK library)
- Stopwords Removal (removing most common words from sentences)
- Various other techniques (spell correction, sentiment analysis, part-of-speech tagging).
- Recurrent Neural Networks (RNNs) for text classification
- Transformer architectures (attention is all you need)
- Writing Python code to leverage transformers (BERT | spacy-transformers)
- Writing a classification model using transformers/BERT
- Fine-tuning transformer models
