Complete Natural Language Processing Tutorial in Python
Offered By: Keith Galli via YouTube
Course Description
Overview
Syllabus
- 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
- Predicting new utterances classes using our model transform
- 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
- 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
- Bring it all together and build a high performance model to classify the categories of Amazon reviews!
Taught by
Keith Galli
Related Courses
Artificial Intelligence for RoboticsStanford University via Udacity Intro to Computer Science
University of Virginia via Udacity Design of Computer Programs
Stanford University via Udacity Web Development
Udacity Programming Languages
University of Virginia via Udacity