- Learn basics of NLP
- Build a NLP pipeline
A. Text Processing
B. Feature Extraction
C. Modeling
- Cleaning
- Normalization
- Tokenization
- Stop Word Removal
- Part of Speech Tagging
- Named Entity Recognition
- Stemming and Lemmatization
- Bag of Words
- TF-IDF
- Word Embeddings
The final stage of the NLP pipeline is modeling, which involves devising a statistical or machine learning model, fitting its parameters to training data, using an optimization procedure, and then using it to make predictions on unseen data.
The nice thing about working with numerical features is that it allows you to choose from all machine learning models or even a combination of them. Once you have a working model, you can deploy it as a web app, mobile app, or integrate it with other products and services. The possibilities are endless.