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statsandr.com | ||
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poissonisfish.com
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| | | | | It has been well over a year since my last entry, I have been rather quiet because someone has been rather loud ?? Just last week I found some time to rewrite a draft on gradient descent from about two years ago, so here we are - back in business! Gradient descent is a fundamental... | |
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www.rdatagen.net
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| | | | | In my previous post, I described a continuous data generating process that can be used to generate discrete, categorical outcomes. In that post, I focused largely on binary outcomes and simple logistic regression just because things are always easier to follow when there are fewer moving parts. Here, I am going to focus on a situation where we have multiple outcomes, but with a slight twist - these groups of interest can be interpreted in an ordered way. | |
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www.listendata.com
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| | | | | [AI summary] The user is seeking guidance on performing linear regression analysis in R, including data preparation, model building, and interpretation. They have questions about multicollinearity, variable selection, and package usage. The response should provide step-by-step instructions on installing necessary packages, conducting analysis, and addressing common issues. | |
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sirupsen.com
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| | | [AI summary] The article provides an in-depth explanation of how to build a neural network from scratch, focusing on the implementation of a simple average function and the introduction of activation functions for non-linear tasks. It discusses the use of matrix operations, the importance of GPUs for acceleration, and the role of activation functions like ReLU. The author also outlines next steps for further exploration, such as expanding the model, adding layers, and training on datasets like MNIST. | ||
