Classical ML vs. Deep Learning

What is the difference betwenn Classical ML & Deep Learning?

All deep learning algorithms are machine learning algorithms but not all machine learning algorithms are deep learning algorithms.

Deep learning algorithms are based on neural networks and the classical ML algorithms are based on classical mathematical algorithms, such as linear regression, logistic regression, decision tree, SVM, and so on.

Deep learning advantages:

• Suitable for high complexity problems
• Better accuracy, compared to classical ML
• Better support for big data
• Complex features can be learned

Deep learning disadvantages:

• Difficult to explain trained data
• Require significant computational power

Source: Google image

Classical ML advantages:

• More suitable for small data
• Easier to interpret outcomes
• Cheaper to perform
• Can run on low-end machines
• Does not require large computational power

Classical ML disadvantages:

• Difficult to learn large datasets
• Require feature engineering
• Difficult to learn complex functions

Ressources:

Deep Learning vs. Machine Learning: A Simple Explanation | Hacker Noon

Deep Learning vs Classical Machine Learning

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