Deep Learning  Vs  Machine Learning

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What's the difference?

What is Machine Learning?

As a subfield of artificial intelligence, ML is concerned with the ability of machines to learn without being explicitly programmed. The goal is for machines to learn on their own.

Still shot of laptop displaying a coding sequence.

Still shot of laptop displaying a coding sequence.

What is Deep Learning?

As a subfield of ML, deep learning is concerned with machines' ability to mimic the human brain in order to perform highly complex tasks related to artificial intelligence.

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Head-to-Head Comparison: Data Feeding

Structured data are fed to the machine that develops the ML model.          Deep learning involves feeding unstructured data, or raw input to the neural network.

Close-up shot of a computer screen scrolling down to show coding.

Close-up shot of a computer screen scrolling down to show coding.

Head-to-Head Comparison: Human Involvement

ML models are easy to build, but better predictions require more human intervention.  Deep learning models are difficult to build, but it’s more accurate without human intervention.

Close-up shot of hands typing on a Macbook keyboard.

Close-up shot of hands typing on a Macbook keyboard.

Head-to-Head Comparison: Volume of Data

A ML model can handle datasets with thousands of rows of data.           A deep learning model typically deals with datasets that have millions of rows of data.

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To view a detailed comparison of Machine Learning and Deep Learning, Click here…