Hi mentor,
I have some basic Python coding skills, to make the most of this course please advise on:
Q1: How well do we need to understand the coding in the lab in order for me to build something on my own after completing MLS? Should I be concerned as I don’t fully understand how most variables been defined and how it produced the results?
For example, from lab_utils_multi import zscore_normalize_features, run_gradient_descent_feng
from lab_utils_multi import norm_plot, plt_equal_scale, plot_cost_i_w
here, I don’t understand how all those variables have been defined in the back end?
Q2: In C1_W2_lab04 what codes can plot the cost vs iteration like it did in lab03?
Many thanks
Christina
Yes, you should be concerned, if you want to work on your own after you complete the course.
Importing packages gives you access to the functions defined in those files. All of those items are function names.
For example, you can read those functions by opening the lab_utils_multi.py file, you can find it via the Files menu in the notebook.
I can’t answer your 2nd question without taking some time to read those labs. But you can read the labs yourself and get some answer via your own research.
Hi Tom, many thanks for your swift response. Much appreciated. To what level of coding skills should I gain in order to work on my own/build a basic model as a ML practitioner? Do you have any suggestions on what I need to do to get there?
I don’t seem to be able to find the lab_utils_multi.py file via the Files menu in the notebook? I’d appreciate if you could please point me there or provide more details?
Thanks,
Christina
I recommend you attend some Python tutorial courses. Then as you complete the Machine Learning Specialization, you should get an idea which areas you need to study further.
Once you open the Files menu, then you use Open. This will display a list of files. You can click on any of the .py files, and they will open in the browser so you can read them.