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r-spatial.github.io
| | josiahparry.com
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| | sfdep.josiahparry.com
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| | [AI summary] This post details the features of version 0.2.4 of the 'sfdep' R package, focusing on new capabilities for spatio-temporal and colocation analysis, as well as point-pattern utilities.
| | www.r-spatial.org
5.3 parsecs away

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| | Spatial networks in R with sf and tidygraphLucas van der Meer, Robin Lovelace & Lorena AbadSeptember 26, 2019
| | jaketae.github.io
33.4 parsecs away

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| Recently, a friend recommended me a book, Deep Learning with Python by Francois Chollet. As an eager learner just starting to fiddle with the Keras API, I decided it was a good starting point. I have just finished the first section of Part 2 on Convolutional Neural Networks and image processing. My impression so far is that the book is more focused on code than math. The apparent advantage of this approach is that it shows readers how to build neural networks very transparently. It's also a good introduction to many neural network models, such as CNNs or LSTMs. On the flip side, it might leave some readers wondering why these models work, concretely and mathematically. This point notwithstanding, I've been enjoying the book very much so far, and this post is...