How does deep learning differ from traditional machine learning?

The question is about deep learning

Answer

Deep learning differs from traditional machine learning in its ability to automatically extract features from raw data through neural networks. While traditional machine learning often requires manual feature extraction, deep learning models can learn hierarchical features directly from data. This capability allows deep learning to excel in complex tasks like image and speech recognition. However, deep learning models typically require more data and computational resources, making them more resource-intensive compared to traditional machine learning approaches.

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Zeeshan S., Junior Software Engineer - AI, Deep Learning and General Development at Softaims

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