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Easily create machine learning training data
Automate training data labeling using a programmatic approach
developed at the Stanford AI lab
developed at the Stanford AI lab
Accelerate the creation of training data and make the shift to data-centric AI application development with a complete AI development platform built for the enterprise.
Leading enterprises use Snorkel Flow to build industry-specific AI applications that leverage subject matter expertise to quickly label data and iteratively develop end-to-end AI applications.
Our team will show you how Snorkel Flow can enable you to:
- Classify free text or text documents, PDFs, HTML, or structured columnar data—including numeric, text, and categorical—across multiple classes
- Extract named entities such as person or location; or numeric data like currency and dates from text such as news articles, emails, tweets, voice transcripts, PDFs, and HTML
- Understand intents, sentiments, and topics across masses of conversational data by classifying utterances or full conversations
- Link entities by recognizing and disambiguating them for example, company names and ticker symbols
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Technology developed and deployed with the world's leading organizations
How Snorkel Flow works —
An End-to-end ML Platform Centered Around Data
Designed to accelerate AI application development by removing the training data bottleneck.
01
Label & Build
Label and build training data programmatically in hours without months of hand-labeling
02
Integrate & Manage
Automatically clean, integrate, and manage programmatic training data from all sources
03
Train & Deploy
Train and deploy state-of-the-art machine learning models in-platform or via Python SDK
04
Analyze & Monitor
Analyze and monitor model performance to rapidly identify and correct error modes in the data
