Machine Learning vs Deep Learning

Deep learning is a kind of machine learning—not always the better one. Here's what separates them, and when a simpler model wins on real business data.

The relationship

Deep learning is a subset of machine learning that uses neural networks with many layers. All deep learning is machine learning; not all machine learning is deep learning.

	Traditional ML	Deep Learning
Best data	Structured/tabular	Images, audio, language
Data needed	Less	Lots
Cost/compute	Lower	Higher
Explainability	Often easier	Harder

When deep learning wins

Use deep learning for perception and language—images, audio, text—where it clearly outperforms. This powers computer vision and LLMs.

When simpler ML wins

For structured or tabular business data, especially smaller datasets, simpler machine learning is often more accurate, cheaper, and easier to explain. Choosing deep learning by default is a common, expensive mistake—the right-tool discipline.

Match method to problem

The right question isn't "deep learning or not"—it's what fits the data and decision. A strong team picks the simplest method that works, keeping cost and explainability in check.

Why FISTA

FISTA Solutions picks the right method for the problem—deep learning where it fits, simpler ML where it wins—so you don't overpay for complexity, through AI enablement, backed by 150+ projects across 12+ countries.

Not sure which approach fits your data? Talk to FISTA.