4 Essentials for the Data Labeling Pipeline

4 Essentials for the Data Labeling Pipeline

Supervised learning requires a lot of labeled data. Here’s what it takes to design a high-performance data labeling pipeline for machine learning.

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Boiling the Ocean: Processing the Data that Powers AI

Boiling the Ocean: Processing the Data that Powers AI

Even in uncertain times, you’re swimming in an ocean of data. If you’re using AI, how you process and use that data will determine the future of your business.

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Why Using Data Scientists for Data Labeling is a Big Mistake [Infographic]

Why Using Data Scientists for Data Labeling is a Big Mistake [Infographic]

Your in-house data scientists shouldn't be doing tedious data labeling work for machine learning projects. They should be focusing on more important innovation.

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5 Qualities in Good Data Labeling Vendors [Infographic]

5 Qualities in Good Data Labeling Vendors [Infographic]

Not all outsourced data labeling partners are a good fit for every AI project. Here are 5 things you need to consider before, during, and after vendor evaluations.

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In-House vs. Managed Workforce Data Labeling Partner [Infographic]

In-House vs. Managed Workforce Data Labeling Partner [Infographic]

It takes a lot of time and resources to prepare and label data. Learn why outsourcing the data preparation to a managed workforce partner is a good business decision.

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6 Ways Data Labeling Providers Put Your Data Quality At Risk [Infographic]

6 Ways Data Labeling Providers Put Your Data Quality At Risk [Infographic]

The level of data quality you'll receive from data labeling providers depends on several workforce, QA and tooling factors. Here are 6 ways some data labeling providers put your ...

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3 Signs Data Labeling Provider Delivers Quality Data [Infographic]

3 Signs Data Labeling Provider Delivers Quality Data [Infographic]

The people, processes, and tools used by outsourced data labeling partners make a big difference in final data quality. Here are 3 signs that you'll receive quality work from your ...

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High-Quality Data — Challenge Accepted

High-Quality Data — Challenge Accepted

Data quality is clearly paramount for a successful AI project, but how difficult is it to achieve?

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Seeing the Big Picture with Your AI Data

Seeing the Big Picture with Your AI Data

Achieving a high level of accuracy in data labeling is vital. This concept can be understood if we think about a mural of Rubik’s Cubes®.

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How to Solve the Specialization Challenge

How to Solve the Specialization Challenge

Any problem (like a Rubik’s cube®) is solvable with a documented process.

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What You Need to Know to Solve Your Data Puzzle

What You Need to Know to Solve Your Data Puzzle

How solving a Rubik’s cube® is like labeling your unstructured data.

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Seizing Your AI Opportunity Requires Quality Data and Partners

Seizing Your AI Opportunity Requires Quality Data and Partners

CloudFactory partner Scientia shares the AI opportunity and the importance of quality data for machine learning.

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3 Ingredients for Scaling Quality Data Labeling for Machine Learning

3 Ingredients for Scaling Quality Data Labeling for Machine Learning

Gartner predicts 85% of AI projects will fail. One of the leading reasons is low-quality data labeling. High-performing machine learning algorithms require high-quality data. ...

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5 Strategic Steps for Choosing Your Data Labeling Tool

5 Strategic Steps for Choosing Your Data Labeling Tool

Your choices about tooling and workforce will be important factors in your success as you design, test, validate, and deploy any ML model.

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The 3 Hidden Costs of Crowdsourcing for Data Labeling

The 3 Hidden Costs of Crowdsourcing for Data Labeling

Crowdsourcing seems to offer a cheap option for training machine learning models, but it’s rarely as inexpensive as it seems. Here are some of the hidden costs of the crowd.

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AI Challenges And Why Legal Is A Great Place To Kick-Start Great NLP

AI Challenges And Why Legal Is A Great Place To Kick-Start Great NLP

AI makes information easier to find for attorneys and their opponents. That levels the playing field. It fundamentally changes the way work is done in the legal profession, where ...

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