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Source channel @githubtrending · Post #14953 · Jul 13

#python#documentation#gotchas#interview_questions#pitfalls#python#python_interview_questions#snippets#wats#wtf Python is a high-level, easy-to-read programming language widely used in many fields like web development, data science, and AI. The "What the f*ck Python?" project helps you understand tricky, surprising Python behaviors through clear examples and explanations. It reveals lesser-known features and common pitfalls, making it easier to write better code and debug problems. By exploring these examples, you can deepen your knowledge of Python’s internals, improve your coding skills, and avoid common mistakes, which benefits both beginners and experienced programmers alike[3]. https://github.com/satwikkansal/wtfpython

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djangoproject

@djangoproject · Post #274 · 03/18/2017, 01:48 AM

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https://github.com/riga/tfdeploy Google's TensorFlow framework is taking off big-time now that it's at a full 1.0 release. One common question about it: How can I make use of the models I train in TensorFlow without using TensorFlow itself? #Tfdeploy is a partial answer to that question. It exports a trained TensorFlow model to "a simple #NumPy-based callable," meaning the model can be used in Python with Tfdeploy and the the NumPy math-and-stats library as the only dependencies. Most of the operations you can perform in TensorFlow can also be performed in Tfdeploy, and you can extend the behaviors of the library by way of standard Python metaphors (such as overloading a class). Now the bad news: Tfdeploy doesn't support GPU acceleration, if only because NumPy doesn't do that. Tfdeploy's creator suggests using the gNumPy project as a possible replacement. #Machine_learning

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