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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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10 similar posts found

djangoproject

@djangoproject · Post #230 · 01/16/2017, 01:42 PM

http://www.aparat.com/v/0scM5 Irene Chen A Beginner's Guide to Deep Learning. What is #Deep_Learning ? It has recently exploded in popularity as a complex and incredibly powerful tool. This talk will present the basic concepts underlying deep learning in understandable pieces for complete beginners to #machine_learning.

djangoproject

@djangoproject · Post #229 · 01/16/2017, 01:41 PM

http://www.aparat.com/v/Corus Advanced users #Deep_Learning, anyone who has followed #machine_learning over the past years has heard it. In this talk I will go past the hype and show what deep learning actually means and how one goes about solving complex machine learning task with a minimum amount of code, with the help of theano, an amazing python library for deep learning.

djangoproject

@djangoproject · Post #446 · 09/17/2017, 01:05 AM

Time Series Prediction with LSTM Recurrent Neural Networks in Python with Keras Time series prediction problems are a difficult type of predictive modeling problem. Unlike regression predictive modeling, time series also adds the complexity of a sequence dependence among the input variables. A powerful type of #neural_network designed to handle #sequence dependence is called #recurrent_neural_networks . The Long Short-Term Memory network or LSTM network is a type of recurrent neural network used in #deep_learning because very large architectures can be successfully trained. https://machinelearningmastery.com/time-series-prediction-lstm-recurrent-neural-networks-python-keras/

djangoproject

@djangoproject · Post #413 · 08/15/2017, 12:34 PM

http://codeinpython.com/tutorials/deep-learning-tensorflow-keras-pytorch/?nonamp=1 Deep Learning #Tensorflow vs #Keras vs #PyTorch #Deep_learning is the application of artificial #neural_networks (ANNs) to learn tasks. These tasks contain more than one hidden layer. Deep learning is part of a broader family of #machine_learning. Machine learning itself is a part of #Artificial_Intelligence(#AI).

djangoproject

@djangoproject · Post #584 · 03/22/2018, 11:01 AM

https://hackernoon.com/absolute-fundamentals-of-machine-learning-dca5deee78df?gi=2c99287cb9f5 #machine_learning , what a buzzword. I’m sure you all want to understand machine learning, and that’s what I’m going to teach in this article. I found that learning the theroetical side alongside the programming side makes it easier to learn both, so this article features both easy to understand mathematics and the algorithms implemented in Python. Also, technology becomes outdated — fast. The code used in this tutorial will likely be meaningless in 5 years time. So for that reason, I’ve decided to also teach the mathematical side to Machine Learning that will not die out in a few years.

djangoproject

@djangoproject · Post #278 · 03/18/2017, 02:02 AM

https://github.com/pytorch/pytorch #PyTorch doesn't only port #Torch to Python, but adds many other conveniences, such as #GPU acceleration and a library that allows multiprocessing to be done with shared memory (for partitioning jobs across multiple cores). Best of all, it can provide GPU-powered replacements for some of the unaccelerated functions in #NumPy. #machine_learning

djangoproject

@djangoproject · Post #445 · 09/17/2017, 01:01 AM

https://machinelearningmastery.com/setup-python-environment-machine-learning-deep-learning-anaconda/ It can be difficult to install a #Python#machine_learning environment on some platforms. Python itself must be installed first and then there are many packages to install, and it can be confusing for beginners. In this tutorial, you will discover how to set up a Python machine learning development environment using #Anaconda.

djangoproject

@djangoproject · Post #251 · 02/02/2017, 06:06 PM

https://www.analyticsvidhya.com/blog/2016/08/deep-learning-path/?utm_content=bufferd56c5&utm_medium=social&utm_source=linkedin.com&utm_campaign=buffer #Deep_Learning, a prominent topic in #Artificial_Intelligence domain, has been in the spotlight for quite some time now. It is especially known for its breakthroughs in fields like Computer Vision and Game playing (Alpha GO), surpassing human ability. Since the last survey, there has been a drastic increase in the trends. (click here to check out the survey) Here is what Google trends shows us: