Article

  1. Data Validation & Relevance

    10 must-know terms and components for search engine development

    Your search engine is often the first interaction a user has with your company. There are many factors that go into making that search engine find and rank results from thousands or even millions of pages in a matter of seconds. Discover ten must-know search engine terms and components.

  2. Linguistic Annotation

    What is natural language processing?

    Natural language processing (NLP) is the term used to describe a machine’s ability to interpret and respond to language data. Learn why it is a key AI concept.

  3. AI Best Practices

    What’s the difference between AI, machine learning and deep learning?

    There are subtle differences between AI and its related fields: machine learning and deep learning. Let’s take a closer look at these terms.

  4. Computer Vision

    What’s the difference between CNN and RNN?

    Discover the difference between CNN and RNN and how they are used in computer vision and natural language processing.

  5. Data Collection

    How much AI training data do you need?

    It’s only logical to ask how much training data you need, but it can be a complicated question to answer. Let’s take a look at why.

  6. Linguistic Annotation

    A beginner's guide to sentiment analysis

    Sentiment analysis involves classifying the subjective, contextual information within text data. Read our beginner’s guide to learn more.

  7. Data Annotation

    Five types of image annotation and their use cases

    Wondering which image annotation types best suit your project? In this article, we introduce five types of image annotation and their applications.

  8. Data Annotation

    What is text annotation? Five different types of annotations

    To train NLP algorithms, large annotated text datasets are required. Learn more with a brief introduction to five common types of text annotation.

  9. AI Best Practices

    How humans-in-the-loop improve map and navigation software

    Discover three critical ways human-annotated data improves map and navigation software.

  10. AI Use CasesHealthcare

    Machine learning in medicine: Learning to trust

    Trust is fundamental to any use of machine learning — healthcare is no exception. Read on as we look at trust and machine learning in medicine.

  11. Data Annotation

    How to get annotated data for machine learning

    Capturing enough accurate, quality data at scale is a common challenge. Discover four ways to source raw data for machine learning, and how to go about annotation process.

  12. AI Use Cases

    AI in retail: Technologies and applications

    AI in retail offers a multitude of benefits, but how does it work? We look at examples of retail automation and the technology that powers it.

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