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Building a simple, not-so cool ML Model - Polynomial Fitting

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Polynmial-Fitting

To understand Polynomial Fitting, I've created a basic model from scratch.

Problem : Given a data set of web status which contains number of requests per hour. Task is to find when the number of web hits would reach 1,00,000.

  1. Reading and visualizing the data - done in the ch1.py file
  2. creating the error function - in ErrorFn.py file
  3. finding the best polynomial function - in segregatingData.py file
  4. Testing the model using the web_test dataset.
  5. Calculating when the web-hits would reach 1,00,000 per hour - result.py

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Building a simple, not-so cool ML Model - Polynomial Fitting

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