Beginner guides, Windows, networking, and more Ansible news

Beginner guides, Windows, networking, and more Ansible news: We've mentioned it before in Ansible around the web, but there are big changes afoot with Ansible itself.

We've mentioned it before in Ansible around the web, but there are big changes afoot with Ansible itself and the move to collections. To keep the developer community updated with the rate of progress, our own Greg DeKoenigsberg has started a newsletter, The Bullhorn. You should check it out!

Continuing with April's wander around the web, we found articles on Windows packages, Oracle, configuration verification and even managing Excel spreadsheets. Enjoy!

If you spot an interesting Ansible story on your travels, please send us the link via Mark on Twitter, and the Ansible Community team will curate the best submissions.

Articles

ManageIQ + Ansible, Windows packaging, linting, verification and more:

Ansible is now embedded in ManageIQ

Ansible automation with Chocolatey for Windows package installs

Fully automated Oracle 18XE build with Ansible

Using Ansible to verify configurations

Ansible linting with GitHub Actions

Managing Microsoft Excel Sheets from within Red Hat Ansible

neural networks

Neural networks, as their name implies, are computer algorithms modeled after networks of neurons in the human brain. Learn more about neural networks from Algorithmia.

Recurrent neural networks, also known as RNNs, are a class of neural networks that allow previous outputs to be used as inputs while having hidden states.

The purpose of this project is to build and evaluate Recurrent Neural Networks(RNNs) for sentence-level classification tasks. Let's understand about recurrent neural networks for multilabel text classification tasks.

Artificial neural networks (ANNs), usually simply called neural networks (NNs), are computing systems vaguely inspired by the biological neural networks that constitute animal brains.

Convolutional Neural Network: How is it different from the other networks? What’s so unique about CNNs and what does convolution really do? This is a math-free introduction to the wonders of CNNs.