hello,
i am a complete beginner in ML, i did not understand how the code is running in the model representation lab, can anyone help me or tell me what i should do?
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Hey @Prayas_Bhende,
Welcome to the community. I guess you have posted your query in the wrong place. Can you please tell us which specialization, which course, which week, and which assignment are you referring to?
Regards,
Elemento
Hello @Elemento ,
Thank you for the reply,
I am referring to Machine learning specialization, supervised machine learning: regression and classification course, week 1, optional lab: Model representation
I did not quite understand the optional lab, to be specific i did not understand how the code was working, I don’t know a lot about libraries in python
I am sorry for improper placement of the query
regards,
prayas
Hey @Prayas_Bhende,
No worries regarding this. I just moved this to its appropriate category for you. Now, let’s come to your query. Let’s deal it step-by-step. Learning about libraries in Python can indeed be daunting for a new learner, but we have to start somewhere and sometime. So, let’s start here and now. According to me, there are N number of libraries in Python, and each of them is best in what it does, but this specialization, heavily exploits only a number of them. To narrow down our focus further, MLS C1 uses 3 libraries in general:
- Numpy, learn here
- Matplotlib, learn here
- Scikit-Learn, learn here
For all the 3 libraries, I have mentioned the link to their “Getting Started” resources. You can’t find better tutorials and examples to learn about these libraries anywhere on the web, since these have been created by the creators of the libraries themselves. You can make yourself comfortable with these tutorials, and after that, you can proceed with the course. This way, you won’t have to search about the most fundamental functionalities that these libraries offer, and the ones you won’t get to learn about in these tutorials, you will know where to find about them.
Another way would be to intermix your “getting familiar with tutorials” and “proceeding with the course”, i.e., learn as you go. You will the references to all the relevant functions of these libraries that are used in the graded and ungraded labs, so you can simply look up each of them as you encounter each of them.
Now once you have done this, I am sure understanding these labs would be much easier for you, and if you face any issues with any specific part of any specific lab, you can always search for a similar issue first, and if you are unable to find one, you can always create a new issue. We, the mentors, would be more than happy to help you out with your issues. All the best 
Regards,
Elemento