A recommender system uses machine learning to predict the likelihood that a user will prefer a particular item or service. Learn how these systems facilitate great experiences that keep customers coming back for more.
The best way to avoid haphazard automation efforts is to put a detailed roadmap in place. Discover expert tips for developing a plan and putting it in action.
More and more brands are using machine learning and computer vision in their advertising. Discover the risks and benefits.
If you train your model with biased data, it will learn and even amplify those biases. Here’s how to address bias in artificial intelligence models.
Uncover the history of computer vision, deep learning and neural networks, and learn how their developments could meaningfully impact businesses and society as a whole.
There are a wide variety of audio transcription services. In this article, we’ll help you to figure out which type of audio transcription is best for you.
When most people think of AI, they think of computers and exuberant datasets. But humans are the most critical piece of any AI project. Learn why.
Discover what data annotation is, why it’s important and the key types of data annotation processes that help fuel our AI-driven world.
Every AI and machine learning project requires training in order to excel. Learn what AI training is, how it works and discover some tips for success.
Discover five of the most common pitfalls brands encounter with data collection — and ways to successfully overcome them.
Learn about how data scientists use large volumes of annotated data to improve the decision-making of AI models.
Humans and animals use their eyes to see the world around them; computer vision is the science that aims to give a similar skill to machines. Learn how in this overview.
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