Machine Learning Accelerator

Natural Language Processing

Overview

Techniques

Model Types

Model Evaluation

Applications

Overview

Natural Language Processing is an area of machine learning concerned with programming computers to process natural language data.

Examples of processes include parsing, tagging, and sentiment analysis.

Techniques

Main ML Techniques:

• Supervised
• Unsupervised

Data Preprocessing Techniques:

• Impute nulls
• Balance classes
• Normalize

Techniques

Text Processing Techniques:

• TFIDF
• Tokenizing
• Bag of Words
• N-grams
• Stop words
• Stemming

Model Types

K-Nearest Neighbors

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Naive Bayes

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Decision Tree

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Random Forest

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Linear Regression

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Stochastic Gradient Descent

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Neural Nets

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Applications

Hazmat

• Bear Spray

Waste

• Inventory forecasting

Title Text

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Title Text

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