| description | Often companies ask to code different Algorithms from scratch as a part of their craft demo round. |
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The general steps are as follows:
- Get 3 things: The formula for the algorithm, the cost function, the derivatives to be used for gradient descent.
- Initialize the weights and bias.
- In the fit function set the loop to update the weights in each iteration as per the cost function optimization algorithm.
- Create a predict function to predict the values.
- Create a test dataset to test if your function works properly.
- Plot the results.