We recommend LibHunt Ruby for discovery and comparisons of trending Ruby projects. Also, to find more open-source ruby alternatives, you can check out libhunt.com/r/rails
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Based on our record, Ruby on Rails should be more popular than Deep playground. It has been mentiond 121 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
Ruby on Rails, in my opinion, is the most productive full-stack web framework to-date. - Source: dev.to / 6 days ago
Let’s look at two technical solutions — RSCSS/ITCSS. This is indeed a perfect combination of instruments which we use in our projects built on React and Ruby on Rails. - Source: dev.to / 14 days ago
A 7.1 Ruby on Rails application hosted on a Hetzner VPS and deployed via Kamal. - Source: dev.to / 22 days ago
Industry adoption - Without including the adoption of other popular and more established frameworks like Python, React, C#, and others, if we consider the adoption of Ruby frameworks, Rails easily eclipses Hanami. The Rails homepage lists some big-name organizations using the framework. On the other hand, as the new kid on the block, Hanami is not so widely adopted. We'll have to wait and see whether that will... - Source: dev.to / 21 days ago
Here's a real life example: Imagine a Ruby on Rails app on which a team of developers are working. The code is hosted on GitLab and all the work is coordinated using GitLab issues. In other words: For every commit, there's an associated issue and the issue number acts as a sort of primary key for documentation, time reporting and so forth. This convention has a few advantages, most notably the ability to easily... - Source: dev.to / about 2 months ago
Not the parent, but NNs typically work better when you can't linearize your data. For classification, that means a space in which hyperplanes separate classes, and for regression a space in which a linear approximation is good. For example, take the circle dataset here: https://playground.tensorflow.org That doesn't look immediately linearly separable, but since it is 2D we have the insight that parameterizing by... - Source: Hacker News / 3 months ago
For visualisation and some fun: http://playground.tensorflow.org/. - Source: dev.to / 5 months ago
Https://seeing-theory.brown.edu/ https://www.3blue1brown.com/ https://playground.tensorflow.org/. - Source: Hacker News / 9 months ago
There’s an interactive neural network you can train here, which can give some intuition on wider vs larger networks: https://mlu-explain.github.io/neural-networks/ See also here: http://playground.tensorflow.org/. - Source: Hacker News / 11 months ago
This site is worth playing around with to get a feel for neural networks, and somewhat about ML in general. There are lots of strategies for statistical learning, and neural nets are only one of them, but they essentially always boil down into figuring out how to build a “classifier”, to try to classify data points into whatever category they best belong in. Source: 11 months ago
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