I am confused on differentiating deep learning and machine learning. Can someone please help me to give an idea about it.

Machine learning in simpler terms is a way to train a machine for a certain task be it classification, regression, etc based on the features provided for the model to train.

Deep learning however, learns those features from the data by itself. Hope this helps!

A major difference to add here is that Machine Learning is more oriented towards statistical algorithms, (ML also has learning algorithms) whereas Deep Learning is usually Neural Networks training based.

Among These ML and DL which one is superior / better?

Which is often used by big companies?

I think Machine Learning is a broader term (superset) as compared to Deep Learning.

Machine Learning can be done in several ways: Classical Machine learning approaches examples can be Linear Regression, Logistic Regression, Support Vector Machine etc. Whereas newer Machine Learning approaches are based on Neural network like Deep learning.

As the size of available training data increases, neural network based approaches do better.

If the training data is not that much (can happen), a classical approach might do equally better or may even outperform a neural network based approach.

Both the classical and newer approaches.