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d2l.ai | ||
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blog.fastforwardlabs.com
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| | | | | The common approach in machine learning is to train and optimize one task at a time. In contrast, multitask learning (MTL) trains related tasks in parallel, using a shared representation. One advantage of MTL is improved generalization - using information regarding related tasks prevents a model from being overly focused on a single task, while it is also learning to produce better results. MTL is an approach, and is not restricted to any particular algorithm. | |
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matthewearl.github.io
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dennybritz.com
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| | | | | Deep Learning is such a fast-moving field and the huge number of research papers and ideas can be overwhelming. | |
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blog.fastforwardlabs.com
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| | | By Chris and Melanie. The machine learning life cycle is more than data + model = API. We know there is a wealth of subtlety and finesse involved in data cleaning and feature engineering. In the same vein, there is more to model-building than feeding data in and reading off a prediction. ML model building requires thoughtfulness both in terms of which metric to optimize for a given problem, and how best to optimize your model for that metric! | ||
