Welcome to your first (required) programming assignment of Course 1 of the Deep Learning Specialization! You'll be building a logistic regression classifier to recognize cats (meow!). This assignment will step you through how to do this with a Neural Network mindset, and so will also hone your intuitions about deep learning. By the end of this notebook, you'll be able to classify your own photo as cat/not cat (meow?).
Instructions:
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Do not use loops (for/while) in your code, unless the instructions explicitly ask you to do so.
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Some code blocks contain graded functions, where you’ll be expected to write some code. These are marked at the top of the block by a #GRADED FUNCTION comment, and you’ll write your code in between the ### START SOLUTION HERE ### and ###END SOLUTION HERE### comments. Also, look for another comment that indicates roughly how many lines of code it will take to complete. After coding your function, run the cell right below it. This cell checks whether your results are correct, and cannot be modified.
When you run that cell and see the following:
"All tests passed."
...You’re in good shape. :)
Take your time to complete this assignment! After you are done, submit your work and check your results. You need to score 70% to pass. Good luck! :)