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Machine Learning may be a subfield of computer science that allows machines to boost at given tasks with experience. it\'s one of the best applications of AI that enable the machines to automatically learn and improve without being explicitly programmed. Another important point to be noted is that every machine learning technique is classified as AI ones. However, not all AI could count as machine learning. Human knowledge is barely obtained by the experience throughout their life. For machines that knowledge is required to be fed by collecting enormous amounts of information on a specific application and fed thereto, machines also obtain in an exceedingly short period of your time. Machine learning lifecycle goes this, firstly it gathers data, then prepare the info, then data-wrangling occurs, then analyze the info and train the model, then testing of model and therefore the most vital and the last step is Deployment.

questions

Title
Which of the following is NOT supervised learning?
Suppose we would like to perform clustering on spatial data such as the geometrical locations of houses. We wish to produce clusters of many different sizes and shapes. Which of the following methods is the most appropriate?
What is the purpose of performing cross-validation?
How do you handle missing or corrupted data in a dataset?
total questions: 24

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