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Answer:
1) Collection is the first stage of the cycle, and is very crucial, since the quality of data collected will impact heavily on the output. ... 2) Preparation is the manipulation of data into a form suitable for further analysis and processing.
2)Data cleansing or data cleaning is the process of detecting and correcting (or removing) corrupt or inaccurate records from a record set, table, or database and refers to identifying incomplete, incorrect, inaccurate or irrelevant parts of the data and then replacing, modifying, or deleting the dirty or coarse data.
3)never reached
4)model is then used as the deployment entity which takes any input in future and produces an output prediction.
Algorithm in machine learning is used to produce an output deployable executable Model, which can be used in future to predict