Machine Learning Accelerator
Natural Language Processing
Overview
MLA Project
Techniques
Modeling
Applications
Overview
Natural Language Processing is an area of machine learning concerned with programming computers to process natural language data.
MLA Project
Objective
Given a product review, predict whether the product is a safety hazard
Dataset
Product reviews with id, date, review, review title, and star rating
Tasks
Preprocess data, process text, build model, train model, evaluate model results, make predictions
Techniques
Techniques for working with natural language data include:
- Pre-processing
- Post-processing
- Feature Engineering
- Dimensionality Reduction
Modeling
Models used for NLP include:
- K-Nearest Neighbors
- Naive Bayes
- Linear Regression
- Stochastic Gradient Descent
- Neural Networks
Applications
General applications include:
- Sentiment analysis
- Text Suggestion
- Entity recognition
- Translation
- Summarization
Specific applications include:
- Hazmat
- Bear Spray
- Material Classification
- Waste processing (bucketing/binning)
