Tips for Machine Learning with Linear Regression in python

I have completed Andrew Ng’s first two weeks content on Linear Regression. I have not started the third week’s content which is on Classification. The reason why I have not opened it because before going into classification, I want to accomplish a couple of good projects (of course guided) and atleast one independent project in Linear Regression. I want to go slow but strong. Can you please help me with your suggestions and guidance. Regards and respect,

Linear regression projects should be very easy to accomplish, if I was you I would try and finish the specialization first and then try to build a meaningful project!

Thank you. But by that time, will I not forget most of the nitty gritties of Linear Regression?

No, its not that long of time and even if you do, you can come back to it again!

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I am on the verge of completing “Supervised Machine Learning - Regression and Classification” course. Just the last quiz is left, which I will complete by tonight. I wanted to ask what next? Should I start building something? If yes, what? Other should I continue with the remaining two courses without wasting time.

This is a personal choice and thought, but I would finish the entire specialization first if I were you. Perhaps even do the deep learning specialization before attepting projects.

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Thank you so much. I value your advice highly. I will follow your advice.

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