Analyze Your Data

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23 articles in this collection
Written by Christine Auld and Steven Auslander

Neural Topic Model (NTM)

Perform a neural topic analysis on your unstructured textual data.
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Written by Steven Auslander
Updated over a week ago

Train a Model on a Subset of Data

When creating a model, you can add a filter to restrict the data that is used for training the model.
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Written by Christine Auld
Updated over a week ago

Retrain a Model

When new data is added to a stream, the new data is automatically analyzed using all of the models that are attached to the stream.
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Written by Christine Auld
Updated over a week ago

Pre-trained Models: Sentiment Predictive Model (Neural Network)

Perform a neural sentiment analysis on your unstructured textual data.
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Written by Christine Auld
Updated over a week ago

Advanced Features: Customize Stopwords Lists

Create custom stopword lists to filter out noise in your data
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Written by Christine Auld
Updated over a week ago

Advanced Features: Customize sentiment dictionaries

Learn how to create a custom sentiment score dictionary
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Written by Christine Auld
Updated over a week ago

Analyzing Data: Overview

This article covers how to interpret the data generated by our analytics engine and how to interact with your data.
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Written by Christine Auld
Updated over a week ago

Unsupervised NLU Model for Analyzing Data

The Unsupervised NLU model is designed to automatically analyze large textual datasets and discover topics and themes.
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Written by Christine Auld
Updated over a week ago

Geo Tag Analysis

Geo maps let you identify clusters of spatial data so you can visualize behavior patterns that might otherwise go unnoticed.
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Written by Christine Auld
Updated over a week ago

N-Gram Generator

The N-Gram Generator is what provides the raw n-gram data for the Unsupervised NLU model.
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Written by Christine Auld
Updated over a week ago

Schedule Data Crawls

Learn to schedule recurring data crawls within your data stream.
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Written by Christine Auld
Updated over a week ago

Stratifyd AI Models

Learn about Stratifyd's AI Models and how they work.
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Written by Christine Auld
Updated over a week ago

Sentiment Analysis

You can use sentiment analysis to determine positive, negative, or neutral attitudes expressed by users.
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Written by Christine Auld
Updated over a week ago
Custom Supervised Models

Supervised Models Overview

Models within this category apply machine learning to your data. Except for AutoLearn, each has a different algorithm.
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Written by Christine Auld
Updated over a week ago

Creating Supervised Models from a Dashboard

Follow these steps to create any of the supervised models within your dashboard.
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Written by Christine Auld
Updated over a week ago

Creating Supervised Models from the Models Page

Follow these steps to create any of the supervised models from the Models page.
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Written by Christine Auld
Updated over a week ago

AutoLearn Model

AutoLearn builds custom machine learning models based on your data and chooses the most suitable ensemble of models based on the F1 score.
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Written by Christine Auld
Updated over a week ago

Feedforward Neural Network Model

The Feedforward Neural Network returns a non-linear decision function. This works well when you have large dataset.
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Written by Christine Auld
Updated over a week ago

Logistic Regression Model

Learn about Logistic Regress, which is a supervised model.
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Written by Christine Auld
Updated over a week ago

Support Vector Machine Model

Learn about the Support Vector Machine, which is a supervised model.
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Written by Christine Auld
Updated over a week ago

Embedding Attentive Model

Learn about the Label-Embedding Attentive Model, which is a supervised model.
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Written by Christine Auld
Updated over a week ago

Random Forest Model

Learn about the Random Forest Model, which is a supervised model.
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Written by Christine Auld
Updated over a week ago

ZSL Model

Models within this category apply machine learning to your data. Except for AutoLearn, each has a different algorithm.
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Written by Christine Auld
Updated over a week ago