58. Differentiate AI, ML, and DL.

1. Artificial Intelligence

AI contains the algorithms and techniques for enabling a machine to perform the tasks commonly linked with human intelligence. The AI applications are trained for processing large amounts of complex information and right decisions without human intervention. For example, chatbots, Space rovers, and Simulators for mathematical and scientific purposes.

2. Machine Learning

This is a subset of Artificial Intelligence and is mainly used for improving computer programs through experience and training on different models. There are three main methods of Machine Learning:

• Supervised learning refers to a type of Machine learning in which the machine requires external supervision for learning from data. It contains the models which are trained using the labeled dataset. Moreover, it solves problems like regression and classification.
• Unsupervised learning refers to a type of machine learning in which the machine does not require any external supervision for learning from the data. This can be trained using the unlabelled dataset. And, it using for solving problems like association and clustering problems.
• Reinforcement Learning is an agent link with its environment by producing actions, and learn with the help of response. The feedback is provided to the agent in the form of rewards like for every good action, the agent gets a positive reward, and for every bad action, there is a negative reward. This uses the Q-Learning algorithm.

3. Deep Learning

Deep Learning adapts to the changes by updating the models depending on constant feedback. This is facilitated by the Artificial Neural Networks that copies the cognitive behavior of the human brain.