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Practical Dependent Types in Haskell 2: Existential Neural Networks and Types at Runtime ยท in Code
| | neuralnetworksanddeeplearning.com
Neural networks and deep learning
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| | [AI summary] The provided text discusses the implementation of a neural network using Theano, focusing on the structure of the network, its layers (FullyConnectedLayer, ConvPoolLayer, SoftmaxLayer), and the training process using stochastic gradient descent (SGD). It also references a paper by C. R. Shu et al. on the application of deep learning in medical image segmentation, particularly in brain tumor detection, and highlights the significance of such advancements in the field of medical imaging and diagnostics.
| | serokell.io
Type Witnesses in Haskell
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| | Learn about the concept of type witness and where it can be useful in this blog post on type-level programming in Haskell.
| | serokell.io
How Dependent Haskell Can Improve Industry Projects
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| | In this post, we talk about Dependent Haskell and show how it could be used to simplify and improve the code in a large production codebase.
| | simpleprogrammer.com
Software Developer Skills - The Technical Skills You Need To Have
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| What Languages to Learn, How to Structure Code, Algorithms & Data Structures, Methodologies, Source Control, Object Oriented Design, Frameworks or Stack ...