What are the steps for using a gradient descent algorithm? 1. Calculate error between the actual value and the predicted value2. Reiterate until you find the best weights of network3. Pass an input through the network and get values from output layer.)Initialize random weight and bias5. Go to each neurons which contributes to the error and change its respective values to reduce the error"

Machine learning (ML) is a branch of artificial intelligence that leverages data to improve computer performance by giving machines the ability to "learn", or improve performance — based on the data.

There are four basic approaches to machine learning: supervised learning, unsupervised learning, semi-supervised learning and reinforcement learning.