Machine Learning is a set of algorithms that train on a data set to make predictions or take actions in order to optimize some systems.

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Machine Learning(ML) is a concept which allows the machine to learn from examples and experience, and that too without being explicitly programmed. So instead of you writing the code, what you do is you feed data to the generic algorithm, and the algorithm/ machine builds the logic based on the given data.

It is a subset of artificial intelligence which focuses mainly on machine learning from their experience and making predictions based on its experience.

Some common examples

1. Have you ever shopped anything online? So while checking for a product or items, did you noticed when it recommends for a product similar to what you are looking for? or did you noticed “the person bought this product also bought this” combination of products. How are they doing this recommendation? This is machine learning.

2. Banking- What is Machine Learning Did you ever get a call from any bank or finance company asking you to take a loan or an insurance policy? What do you think, do they call everyone? No, they call only a few selected customers who they think will purchase their product. How do they select? This is target marketing and can be applied using Clustering(grouping). This is machine learning.

How does Machine Learning(ML) Work?

Machine Learning algorithm is trained using a training data set to create a model. When new input data is introduced to the ML algorithm, it makes a prediction on the basis of the model.

The prediction is evaluated for accuracy and if the accuracy is acceptable, the Machine Learning algorithm is deployed. If the accuracy is not acceptable, the Machine Learning algorithm is trained again and again with an augmented training data set.