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Thank you Uriel. Sorry I did not monitor this. |
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About getting the tools
From the same initial assumptions of 00-syllabus.ipynb and to avoid those famous dependency issues 🔥 related to setting up your environment, I'd recommend the following package managers as tools for the not-so-die-hard-programmers:
On Windows:
On macOS:
On Linux:
Code Editors
Before hitting that awesome Jupyter code block, writing your code with a capable text editor can be very helpful as you'll be able to check your it for errors and keep up with Python's language formatting standards.
Suggestions:
If you intend on following up with programming, choosing Vim or Emacs will most surely help your productivity.
About Anaconda
On line 74 of 00-syllabus.ipynb, it's suggested the students install Anaconda as a way of getting the Python-Jupyter resources.
I'd like to differ and recommend the smaller version of Anaconda, Miniconda, which is also readily available at https://conda.io.
Miniconda is considerably smaller than Anaconda and the user can add packages as they're need, where Anaconda has a much larger prepackaged toolchain which most of the time goes on unused.
On the matter of the resources available.
Google offers two very capable free options to the ones already mentioned in line 72 of 00-syllabus.ipynb.
Which have the following attributes.
Technically, those are hosted Jupyter notebook services requiring no initial setup to use while providing free access to Google's computing resources including CPUs, TPUs and GPUs through the web browser.
Additionally one might run those notebooks locally through the
jupyter_http_over_ws
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