What is the difference between machine learning and deep learning?

Machine Learning | Deep learning
Machine Learning is a technique to learn from that data and then apply what has been learned to make an informed decision | The main difference between deep and machine learning is, machine learning models become better progressively but the model still needs some guidance. If a machine-learning model returns an inaccurate prediction then the programmer needs to fix that problem explicitly but in the case of deep learning, the model does it by himself.

Machine Learning can perform well with small size data also | Deep Learning does not perform as well with smaller datasets.

Machine learning can work on some low-end machines also | Deep Learning involves many matrix multiplication operations which are better suited for GPUs.

Features need to be identified and extracted as per the domain before pushing them to the algorithm | Deep learning algorithms try to learn high-level features from data.

It is generally recommended to break the problem into smaller chunks, sol
ve them and then combine the results | It generally focusses on solving the
problem end to end.

Training time is comparatively less | Training time is comparatively more.

Results are more interpretable | Results Maybe more accurate but less interpretable.

No use of Neural networks | uses neural networks.

Solves comparatively less complex problems | Solves more complex problems.