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polukhin.tech | ||
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iclr.cc
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| | | | | [AI summary] This article discusses a new model compression technique for deep neural networks that enables efficient deployment on low-end devices by dynamically adjusting sparsity and incorporating feedback to enhance performance. | |
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www.ethanrosenthal.com
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| | | | | Talk for TWIMLCon 2022. Abstract It's hard enough to train and deploy a machine learning model to make real-time predictions. By the time a model's out the door, most of us would rather move on to the next model. And maybe that is what most of us do, until a couple months or years pass and the original model's performance has steadily decayed over time. The simplest way to maintain a model's performance is to retrain the model on fresh data, but automating this process is nontrivial. | |
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thedarkside.frantzmiccoli.com
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| | | | | The deep learning community has been relying on powerful libraries enabling more than I can dream of in terms of mathematical capabilities. Back in the days, I worked on an artificial neural network project where we implemented the derivatives where we would need them. Seeing those projects made me willing to toy around with their capacities for other models, not necessarily artificial neural... | |
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jrogel.com
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| | | Exciting News! I am thrilled to announce that the Second Edition of my book, "DataScience and Analytics with Python" is now complete!Seven years ago, when the first edition was published, Artificial Intelligence (AI) and Machine Learning (ML) were just starting to gain traction. Since then, we've witnessed an incredible explosion in interest and development in... | ||
