Machine Learning is the subset of AI (Artificial Intelligence). It provides us statistical tool to explore and analyze the data. There are 3 different types in Machine Learning.

(i) Supervised – labeled data.

(ii) Unsupervised – usually solve clustering (based on the similarity of the data, it will try to group the data together) problems.

(iii) Reinforcement / semi-supervised – some part will be labeled and later on, some part of the data will not be labeled.

Deep Learning is a subset of Machine Learning that inspired by the functionality of our brain cells called neurons. It creates architecture called as Multi Neural network architecture. There are 3 different types in Deep Learning.

(i) ANN (Artificial Neural Network) – tries to solve the data where the input is in the form of numbers.

(ii) CNN (Convolutional Neural Network) - tries to solve the data where the input is in the form of images.

(iii) RNN (Recurrent Neural Network) - tries to solve the data where the input is in the form of time series kind of data.

Data Science is a technique, which try to apply all the techniques of Machine learning and Deep learning. Apart from that, it also uses some mathematical tools like statistics, probability, linear algebra and may more.