Types of machine learning problems on the basis of the nature of learning.
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1) Supervised Learning - The computer is presented with the data and desired output and the goal is to make learn a general rule to map inputs to output.🧵🧵🧵🧵 
2) Unsupervised Learning - No labels are given to the learning algorithm, leaving it on its own to find structure in its input. Unsupervised learning can be a goal in itself.🧵🧵🧵
3) Semi-Supervised Learning - Problems where you don't have all data labelled.These problems lies between supervised and unsupervised learning.🧵🧵
4) Reinforcement Learning - This program run in a dynamic environment and learns from the feedback in terms of rewards and punishments as it navigates its problem space.🧵
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