These are the exercise files used for NICF – Natural Language Processing (NLP) with Python for Beginners course.
The course outline can be found in
https://www.tertiarycourses.com.sg/wsq-nlp-deep-learning-python-course.html
Topic 1 Overview of NLP and Deep Learning
- Overview of NLP
- Applications of NLP
- Deep Learning Approach to NLP
- Basics of Recurrent Neural Network (RNN)
- Install Python Packages for NLP – Scikit Learn, Tensorflow, NLTK, Spacy, Gensim
Topic 2 Word Embedding
- Overview of Word Embedding
- Word Embedding Models
- Pre-trained Word Embedding Models
Topic 3 Language Modeling
- Tokenization and Stop Words
- Stemming & Lemmatizing
- Part of Speech & Parsing
- Named Entities Recognition (NER) Extraction
- Language Modeling with n-gram and RNN
- Pre-trained Language Models
Topic 4 Text Classification
- Text Feature Engineering
- Text Processing Pipeline
- Text Classification
Topic 5 Overview of Attention Mechanism
- Encoder-Decoder Models
- Attention Mechanism to Memory Networks
Final Assessment
- Written Assessment(Q&A)
- Practicum Performance