This video by Daniel Bourke breaks down practical steps on how to learning machine learning with Python.
How does one advance from a beginner in python and go beyond the basics.
This video provides some great insights.
Here’s an interesting video from Gyasi Linje on what the top 5 programming languages to learn in 2019 are.
Giles McMullen shares his favorite Python books.
Socratica explores Random Walk and Monte Carlo simulations via Python code in this well-produced video.
Here’s an interesting video chock full of ideas for Python automation projects by Kalle Hallden.
Skip to the 0:53 mark to avoid the long intro.
Check out this tutorial on sockets with Python 3 and the associated source code.
In this hour long tutorial, learn the basics of the NumPy library in this tutorial for beginners.
It provides background information on how NumPy works and how it compares to Python’s Built-in lists.
It starts with the basics of creating arrays and then gets into more advanced stuff. The video covers creating arrays, indexing, math, statistics, reshaping, and more.
Here’s an interesting look at Python from the point of view of a hard core developer – anyone that remembers IRQs has been around a while.
From the video description:
The Python language’s memory model can be deduced from first principles: simply take modern C++ conventions and drive their safety and generality to infinity. But this limiting case generates its own compromises and opens its own categories of possible runtime errors. We will explore the position Python has staked out in the language design space of correctness versus performance, the choices Python programmers make when they need to move closer to C++, and the ways that the C++ community keeps adopting conventions that look suspiciously like Python.
Also, the audio starts around the 9 second mark.
This Python 3 tutorial course aims to teach everyone the basics of programming computers using Python.
The course has no pre-requisites and avoids all but the simplest mathematics.