Natural Language Processing
🤖 ML techniques to understand, interpret, and generate human language data
Notes
It involves tasks such as
- sentiment analysis
- textclassification
- named entity recognition
- QnA’ing
- machinetranslation
NLPpipeline -s in MLOps may include: - textpreprocess -ing -token -ization -vector -ization (e.g., TF-IDF, word embeddings) - modeltraining (e.g., usingNeuralNetworks like LSTM or Transformers), -evaluate -ion -deployment