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blog.ml.cmu.edu | ||
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fodsi.us
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| | | | | [AI summary] The ML4A Virtual Workshop explores how machine learning enhances classical algorithms through data-driven approaches, featuring talks on deep generative models, model-based deep learning, and learning-augmented algorithms. | |
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brenocon.com
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| | | | | [AI summary] The provided text is a collection of comments and discussions from a blog post that originally criticized artificial neural networks (ANNs) in 2008. The comments reflect a range of opinions and debates about the relationship between machine learning (ML) and statistics, with some users defending ML techniques like support vector machines (SVMs), probabilistic graphical models, and deep learning, while others argue for the importance of statistical methods. There are also discussions about the need for better communication between disciplines, the limitations of ML approaches, and the importance of understanding the underlying assumptions of models. The text includes recommendations for textbooks and courses, such as 'All of Statistics' and Andre... | |
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distill.pub
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| | | | | How to tune hyperparameters for your machine learning model using Bayesian optimization. | |
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randalolson.com
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| | | Full stack data scientist, artificial intelligence researcher, and consultant | ||
