Let's set up working place.
Below you will see a list of prerequisites to get started in ML.
Check them out and after you are done with all of them we are ready to get started.
Don't forget to apply all these steps specifically for your own OS (Mac, Windows, Ubuntu).
1) Install IDE (An integrated development environment) for python. IDE is a software application
that helps programmers to develop software code efficiently.
It increases developer productivity by combining capabilities such as software editing,
building, testing, and packaging in an easy-to-use application.
I'm using PyCharm download link for PyCharm.
You can get one of two communities or professional versions. For our
purposes communities version is fine. Also there's a hint, if you are a student you can get a free professional version
for study purposes.
2) Install Python version 3.10 or newer download link for Python.
Python is a programming language that lets you work quickly and integrate systems more effectively.
Now python is totally fine but later on probably some other languages will be used as well.
You can check Python version, write this command in the terminal: python --version.
You should see something like this
Python 3.10.6
3) Create GitHub account. GitHub is a website and
cloud-based service that helps developers store and manage their code, as well as track
and control changes to their code. In the beginning mainly you need such commands as creating a branch and git pull,
git push.
4) Install pip and/or anaconda. PIP is the package installer for Python.
You can use it to install packages from the Python Package Index and other indexes.
Anaconda is a distribution of the Python and R programming languages for scientific computing that
aims to simplify package management and deployment.
You can check pip version: pip --version you should see pip 21.1.2 and same for anaconda: conda --version.
you should see conda 23.5.2.
5) Create Python project in pycharm, set up Python version that you downloaded. Connect it to your GitHub.
Set up a virtual environment for the project and activate it. You can use terminal or user interface in PyCharm for this.
Don't forget to check that you activated it. In terminal you should notice it.
6) Install these python libraries that we will be using during our courses.
Now we are ready for Machine Learning, Let's get started!!!
P.S. This step can be a bit difficult for truly beginners, but this is really half
of job, overcoming this is the most difficult part. Just spent some time on it consciously.
Google it or find more details on YouTube, spend some time on it and just do step by step.