Preprocessing Data For Machine Learning

Machine Learning Data Preprocessing (converting raw data into numbers and vectors/tensors)

[NB]  Machine Learning Data Preprocessing is very important (normally a first step to know before implementing Machine Learning Algorithm)

It is important to format your data so that the Machine Learning algorithm can process the data and predict accurately. One of the problems experienced by Machine Learning Engineers is accurately processing/formatting the data. Machine Learning algorithms understand data in 1's and 0's, this means that if you want to predict which type of flower it is, the data has to be converted into numbers then use other libraries that convert those numbers into an array of arrays. The Arrays of Arrays are normally called vectors (Metrix array), this helps the Machine Learning Algorithms understand data and be able to make an accurate prediction. 

This video explains in detail


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