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Source channel @githubtrending · Post #14747 · May 25

#python#deep_learning#intel#machine_learning#neural_network#pytorch#quantization Intel Extension for PyTorch boosts the speed of PyTorch on Intel hardware, including both CPUs and GPUs, by using special features like AVX-512, AMX, and XMX for faster calculations[5][2][4]. It supports many popular large language models (LLMs) such as Llama, Qwen, Phi, and DeepSeek, offering optimizations for different data types and easy GPU acceleration. This means you can run advanced AI models much faster and more efficiently on your Intel computer, with simple setup and support for both ready-made and custom models. https://github.com/intel/intel-extension-for-pytorch

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djangoproject

@djangoproject · Post #240 · 01/25/2017, 10:03 AM

http://www.aparat.com/v/4nbc9 This talk gives a quick overview of Python's capabilities as a #data_processing and #machine_learning tool through practical examples: gathering data from the web or a local file, validating/modifying it and finally analyzing it to build models for #classification and #prediction#tasks.