Machine-Learning-Guide
thinc
Machine-Learning-Guide | thinc | |
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6 | 4 | |
437 | 2,794 | |
- | 0.5% | |
6.2 | 7.6 | |
4 months ago | 5 days ago | |
Python | Python | |
- | MIT License |
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Machine-Learning-Guide
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I just learned the basics of python. Where can I get started with machine learning?
This Machine learning Guide has a list of courses and tools for machine learning.
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Useful Tools and Resources for Reinforcement Learning
Found a useful list of Tools, Frameworks, and Resources for RL/ML. It covers Reinforcement learning, Machine Learning (TensorFlow & PyTorch), Core ML, Deep Learning, Computer Vision (CV). I thought I'd share it for anyone that's interested
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How to learn Machine Learning? My Roadmap
I would also recommend this Machine Learning Guide. I found it a weeks ago and it has some useful info.
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Useful Tools, Programs, and Resources for AI/ML
Found a useful list of Tools and Programs for Machine Learning/Deep Learning. Looks like it covers Machine Learning, Deep Learning, Computer Vision(CV), and Natural Language Processing (NLP). I thought I'd share it for anyone that's interested.
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Useful Tools and Programs list for AI/ML
Found a useful list of Tools and Programs for AI/ML. Looks like it covers Machine Learning, Deep Learning, Computer Vision(CV), and Natural Language Processing (NLP). I thought I'd share it for anyone that's interested. https://github.com/mikeroyal/Machine-Learning-Guide
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Cool Machine Learning Guide/ Wiki
Machine Learning Guide/Wiki: https://github.com/mikeroyal/Machine-Learning-Guide
thinc
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JAX – NumPy on the CPU, GPU, and TPU, with great automatic differentiation
Agree, though I wouldn’t call PyTorch a drop-in for NumPy either. CuPy is the drop-in. Excepting some corner cases, you can use the same code for both. Thinc’s ops work with both NumPy and CuPy:
https://github.com/explosion/thinc/blob/master/thinc/backend...
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Tinygrad: A simple and powerful neural network framework
I love those tiny DNN frameworks, some examples that I studied in the past (I still use PyTorch for work related projects) :
thinc.by the creators of spaCy https://github.com/explosion/thinc
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good examples of functional-like python code that one can study?
thinc - defining neural nets in functional way jax, a new deep learning framework puts emphasis on functions rather than tensors, I've tested it for a couple of applications and it's really cool, you can write stuff like you'd write math expressions in papers using numpy. That speeds up development significantly, and makes code much more readable
- thinc - A refreshing functional take on deep learning, compatible with your favorite libraries
What are some alternatives?
Text2Poster-ICASSP-22 - Official implementation of the ICASSP-2022 paper "Text2Poster: Laying Out Stylized Texts on Retrieved Images"
quantulum3 - Library for unit extraction - fork of quantulum for python3
pytorch-forecasting - Time series forecasting with PyTorch
jax - Composable transformations of Python+NumPy programs: differentiate, vectorize, JIT to GPU/TPU, and more
pinferencia - Python + Inference - Model Deployment library in Python. Simplest model inference server ever.
horovod - Distributed training framework for TensorFlow, Keras, PyTorch, and Apache MXNet.
prtm - Deep learning for protein science
extending-jax - Extending JAX with custom C++ and CUDA code
igel - a delightful machine learning tool that allows you to train, test, and use models without writing code
dm-haiku - JAX-based neural network library
pytorch-who-is-that-pokemon - All 151 classes pokemon Gen1 classification with torchvision model.
AIF360 - A comprehensive set of fairness metrics for datasets and machine learning models, explanations for these metrics, and algorithms to mitigate bias in datasets and models.