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Machine learning data modeling steps

  1. Defining the problem — there are many business problems but can we convert them as machine learning problem?
  2. Collecting the data— what type of data we have ?
  3. Evaluation success criteria — What defines success for you?
  4. Data features to be used in model creation— which part of the data contribute more
  5. Model creation— Which model should you choose?
  6. Experiment to better the models— How best we can tweak the steps to better model
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