Using PyTorch (and the broader space of machine learning algorithms under the “deep learning” category) really makes me feel like a wizard. But the downside to being Python-dependent is that putting PyTorch stuff into products not easy. I hope PyTorch 1.0 will change that.
Note: This article was not written with Machine Learning in mind, and I will have to re-read the article to better articulate my thoughts on “Machine Learning Wizardry” and juxtapose my own ideas with those of the article author.
Kudos to author: The article’s main metaphor is excellent because it got my creative juices flowing (i.e., brain working at 110% for a few brief moments).
Comments
Using PyTorch (and the broader space of machine learning algorithms under the “deep learning” category) really makes me feel like a wizard. But the downside to being Python-dependent is that putting PyTorch stuff into products not easy. I hope PyTorch 1.0 will change that.
Note: This article was not written with Machine Learning in mind, and I will have to re-read the article to better articulate my thoughts on “Machine Learning Wizardry” and juxtapose my own ideas with those of the article author.
Kudos to author: The article’s main metaphor is excellent because it got my creative juices flowing (i.e., brain working at 110% for a few brief moments).
You can always use ONNX to convert PyTorch trained model to any other format. https://onnx.ai/