Prerequisites for ML

Does this course will cover the Prerequisites like data visualization of python such as matplotlib , numpy and all ?

Hello @Harsh_Jha1,

The course covers Machine Learning concepts. For matplotlib and numpy, you might check out official tutorials listed here.


so should we do Prerequisites and specialization course simultaneously or
we should first complete Prerequisites then to start with Specialization course
If I know basic of python and how to work with python

For matplotlib, you won’t be required to write any visualization code for the completion of the course. Certainly you will see many uses of it, but the point is not to teach how to use matplotlib but for the course team to visually deliver machine learning concepts. This specialization is about Machine Learning instead of visualization, but we use plots to deliver the ideas. I don’t think you need to delay the MLS because of matplotlib.

For numpy, you won’t have to use it extensively but for only a few times and you will be reminded in the exercise’s description or the exercise’s hints. There are two videos about vectorization and a lab that shows some numpy functions that may or may not be used in the course.

The labs in this course will describe the ML concepts covered in the videos. It will use any library suitable and sometimes won’t explain about those libraries nor the functions. However, again, the point is not the library but the concept.

In the assignments, you mostly use only native python function/code, and sometimes numpy but as I mentioned, there will be hints.

I think these are some relevant facts that I can share with you about matplotlib and numpy. For whether to learn them before MLS or not, it’s really your choice because I know some learners really prefer to be able to write every code that comes across them, but if your objective is to grasp the idea about ML, then I think it’s not a bad idea to just start the MLS and learn numpy or matplotlib that you are particularly interested in by googling. However, if you feel more comfortable to first become pretty familiar with the two libraries before starting MLS, that certainly is your choice.

At the end of the day, I think you will learn any new things if you practice them. As for when to learn, it’s totally up to you. Mastering every bit of the matplotlib code written in this course won’t make you a master of ML, and if you have no project that requires to use the matplotlib skills, it’s easy to forget.

it’s your choice!

Generally, “prerequisites” means you should know the material in advance. That’s what “pre-” refers to.

However, I was not able to find anywhere in the course materials that list any official prerequisites.

@Harsh_Jha1, where did you find a list of the items you mentioned?

There are No such official mentioned prerequisites
but for ML these are know prerequisites
so that’s why I have asked

Hi i just started the course after seeing the option lab i.e model representation i kind of feel bad that i dont know python that much i understand some bits of the code but its kind of difficult for me that i only have knowledge regarding c++ so should i first go through python and then start this course because i am confused

Hello @Hamza_Nadeem1,

What doesn’t change is you need to know Python to finish the labs of this course and this course doesn’t teach Python. What’s your own choice is to learn Python first before continuing on this course, or do both in parallel. I had used C++ before I started to learn Python, and in my opinion, Python is super easy as compared to C++ (although you might like C++ more for its control on memory allocation).

So, you will need basic Python syntax, and this course will use some Python libraries: matplotlib, numpy, tensorflow, … As I wrote above, you won’t be required to write matplotlib code nor understand it. For numpy and tensorflow code, sufficient descriptions, hints and/or references are provided before the exercises that require them.

Can you make a decision?


PS: This post is about learning Python.