pytorch-tutorial
InceptionTime
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| pytorch-tutorial | InceptionTime | |
|---|---|---|
| 3 | 2 | |
| 29,128 | 602 | |
| - | - | |
| 0.0 | 3.1 | |
| 9 months ago | 7 months ago | |
| Python | Python | |
| MIT License | GNU General Public License v3.0 only |
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pytorch-tutorial
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PyTorch - What does contiguous() do?
I was going through this example of a LSTM language model on github (link).What it does in general is pretty clear to me. But I'm still struggling to understand what calling contiguous() does, which occurs several times in the code.
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How to 'practice' pytorch after finishing its basic tutorial?
I tried to move straight to practicing implementing papers and trying to understand other people's codes but failed miserably. I feel like there was too much of a gap between the basic tutorial and being able to implement ideas into code....hence the question: Is there any resource/way to practice pytorch in general? I did find this and this, but I just wanted to hear what others have gone through to become better at PyTorch up to the point they can build stuff from their own ideas
- [P] Probabilistic Machine Learning: An Introduction, Kevin Murphy's 2021 e-textbook is out
InceptionTime
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Keras-tuner tuning hyperparam controlling feature size
I would recommend you to read the following paper: https://arxiv.org/abs/1909.04939 and their implementation: https://github.com/hfawaz/InceptionTime . Moreover, check out sktime: https://github.com/sktime/sktime
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How to install many packages without having to allow each one?
I have to install all these packages...
What are some alternatives?
mixture-of-experts - PyTorch Re-Implementation of "The Sparsely-Gated Mixture-of-Experts Layer" by Noam Shazeer et al. https://arxiv.org/abs/1701.06538
sktime-dl - DEPRECATED, now in sktime - companion package for deep learning based on TensorFlow
Conv-TasNet - A PyTorch implementation of Conv-TasNet described in "TasNet: Surpassing Ideal Time-Frequency Masking for Speech Separation" with Permutation Invariant Training (PIT).
sktime - A unified framework for machine learning with time series
pytorch-grad-cam - Advanced AI Explainability for computer vision. Support for CNNs, Vision Transformers, Classification, Object detection, Segmentation, Image similarity and more.
Keras - Deep Learning for humans
BigGAN-PyTorch - The author's officially unofficial PyTorch BigGAN implementation.
tslearn - The machine learning toolkit for time series analysis in Python
bonito - A PyTorch Basecaller for Oxford Nanopore Reads
keras - Deep Learning for humans [Moved to: https://github.com/keras-team/keras]
OpenNMT-py - Open Source Neural Machine Translation and (Large) Language Models in PyTorch
faceswap - Deepfakes Software For All