Machine Learning is heavily computational. You'll need to have some tools to be able to work with machine learning in your own computer. I recommend the following specs:
- Intel core i5 Gen processor
- 4GB of RAM.
- Not necessary but having a GPU is a great advantage. With GPU computations come way faster compared to CPU.
- For storage I’d recommend at least having 250 GB SSD. Having 120 GB is just too little especially when downloading large datasets and installing a plethora of libraries. SSD hard rives allows for faster reads and writes.
I recommend you watch Siraj Raval’s video for a more detailed explanation as to which laptops are good for machine learning.
You should use a Linux based system. It's just so much easier to work with ml especially since you'll be using the terminal aLOT. With Windows, it's not impossible, but it is definitely harder.
- Have python (2.7 or 3.5 or newer) installed and add it to your path.
Install pip after installing python. Watch my tutorial here.
(please subscribe if it helped you. i'll be posting more content this year ✌🏽)
Optionally you can to install a virtual environment. I recommend using virtualwrapper.
With a virtual environment you can easily manage different packages that you install with pip.
- I recommend you also install jupyter notebook.
python -m pip install jupyter
# do python3 if you installed python 3 or greater
With jupyter notebook you can immediately see the result of your code without having to go into a terminal and running python *.py every single time you change a line of code.
- Optionally, you can also use a code editor and a terminal to run your code. I prefer the VSCode editor and the iTerm terminal, though you can also opt in to use the default Terminal in the Mac or Linux or any of your preferred code editors.
Thanks for reading! This is part 3 of a 4 part series. Next we'll talk about getting into the code of machine learning.
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