AutoNLP: Sentiment Analysis in 5 Lines of Python Code
AutoNLP — AutoML of Natural Language Processing
Automated machine learning (AutoML) refers to automating the process of applying machine learning. Automation in AutoML allows non-experts to train machine learning models without requiring becoming an expert in the field.
A typical Natural Language Processing project follows various aspects of the pipeline to train a machine learning model. Various steps in the pipeline conclude as cleaning text, tokenization, stemming, converting to numerical vector, etc, and finally train various models out of it.
What is AutoNLP?
AutoNLP is very similar to AutoML, it automates the process of EDA and text processing and helps data scientists to get the best model. AutoNLP is a function present in the AutoViML framework, built using scikit-learn, NumPy, pandas, and matplotlib. It is designed to build high-performance interpretable models with the fewest variables.
AutoNLP guides a data scientist in:
- Exploratory data analysis of text
- Data Cleaning
- Feature reduction
- Variable Classification
- Produces model performance results as graphs
