Hi. Thank you for checking out my channel. I like all things FOSS and have a particular affinity for Spacemacs, i3, and zsh. I also professionally use python, deep learning, and the robot operating system. In the channel I'm trying to create lessons on how to use a number of these technologies with a laser focus on making the videos as short as they can be.
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Is my understanding correct? Python threads perform tasks concurrently by using single processor core without parallelism. With Python multiprocessing we can spawn multiple processes with different interpreters on different cores and achieve parallelism.
No. Python threads are also running in parallel but are artificially locked to running one at a time. In some cases you can get rid of this lock. With python 3.12 this is about to become a lot simpler
Great video! I'm trying to teach myself Neural Networks and AI, and one of my future projects will be a "snake" playing AI based on a NN. I now have experience with basic multi-layer NNs for classifying images, etc.. What would you recommend as a "next step" to go from classifiers to NN that can play snake, etc., and some learning resources for this? I realize that this video is 4 years old, but just in case you are monitoring the comments, I thought I'd ask. Thanks!
can you help me install python on termux without an error, when i install it i get this error message E: Sub-process /data/data/com.termux/files/usr/bin/dpkg returned an error code (2)
The reason why you haven't met anyone else that uses Redis Simple Cache might be because they just use the Python standard library `functools.lru_cache()`?
I took my own weird route to playing around with this idea.. First, I wrote a more classic rules based bot to play snake, with it's own recursive function to check future choices for dead ends. It's not perfect, but it can often play the game well enough, to fill half the available space with snake before dying to more difficult to avoid dead-ends. I then used that bot to record 10,000 of it's highest scoring games frame by frame, a couple million frames in total, also recording each action it took per frame. Then I fed all that data into a basic neural network, and ran a few hundred training epochs. So far I've gotten the neural network to play the game alright, but only about as good as my bot. heh
1:00 when did you ever do smth computationaly intensive in python? i guess never.... meanwhile me trying to figure out how to run through 2^32 combinations of numbers using python :/
Don't. Pure Python is the wrong language for it. Use numba or cython for a familiar feel. Or learn to use mypyc. Or use a completely different language.
I often have the problem that my functions take objects as input and act on them. I need to build an additional wrapper to encapsulate simple calculations that can be optimized that's somehow annoying.
I usually watch videos in x2 speed, however here I had to put it in 0.5x speed 🤣 I'm discovering both C++ and pybind11 so although it is hard to follow everything yet your explanation is pretty cool as it sums up most of the functionalities available in a short time, I now understand better where I need to start ! thank you
After being skeptical about this library for a while, I've gotten used to it. I've watched many tutorials and read many articles and documentation. After weeks of determination to learn this technique properly,... I have become, comfortably Numba. 🤟
I think it would be helpful to add what kind of tasks can be multi-threaded in Python, since for certain computational tasks, without numba, the GIL would block multiple threads and make processing single-threaded.
