playground
nvim-treehopper
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playground | nvim-treehopper | |
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16 | 6 | |
11,602 | 387 | |
1.0% | - | |
0.0 | 0.0 | |
2 months ago | 2 months ago | |
TypeScript | Lua | |
Apache License 2.0 | GNU General Public License v3.0 only |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
playground
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Why do tree-based models still outperform deep learning on tabular data? (2022)
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 radius would do the trick. Now try doing that in 1000 dimensions. Sometimes you can, sometimes you can't or do want to bother.
- Visualization of Common Algorithms
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Stanford A.I. Courses
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:
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Where have all the hackers gone?
I don't think so. You can easily play around in the browser, using Javascript, or on https://processing.org/, https://playground.tensorflow.org/, https://scratch.mit.edu/, etc.
If anything the problem is that today's kids have too many options. And sure, some are commercial.
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Tech pioneers call for six-month pause of "out-of-control" AI development
You can actually play with training a very simple model in your web browser here to get an idea of how that works. The important part though is that training is kind of a trial and error adjustment process.
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[D] Tools for drawing/visualising Neural Networks that are pretty?
This is pretty cool: https://playground.tensorflow.org/
nvim-treehopper
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Neovim quick way to indent multiple lines
Take a look at nvim-treehopper (https://github.com/mfussenegger/nvim-treehopper), a tree-sitter based plugin that lets you select regions of code
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Leaps and (no) bounds - extend leap.nvim with custom motions, callbacks, Tree-sitter, and more
This copies the idea of nvim-treehopper. Just a work in progress hack (pretty usable though), but planning to make a full-fledged plugin, if someone else won't do it :) (Needless to say, my gists can be considered unlicensed, do whatever you want with them.)
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The most amazing built-in feature nobody ever mentions: smart select!
I also suggest taking a look at this one : mfussenegger/nvim-treehopper
- Bram: "Neovim has included Treesitter, which is an implementation of this. Once Vim9 is done I'll have a look at whether it is a good choice to include with Vim"
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Plugin: treesitter-unit
https://github.com/mfussenegger/nvim-ts-hint-textobject does what you are proposing.
What are some alternatives?
spellsitter.nvim - Treesitter powered spellchecker
nvim-treesitter-context - Show code context
NvChad - An attempt to make neovim cli as functional as an IDE while being very beautiful , blazing fast. [Moved to: https://github.com/NvChad/NvChad]
zephyr-nvim - A dark neovim colorscheme written in lua
nvim-gps - Simple statusline component that shows what scope you are working inside
twilight.nvim - 🌅 Twilight is a Lua plugin for Neovim 0.5 that dims inactive portions of the code you're editing using TreeSitter.
playground - Treesitter playground integrated into Neovim
vim-treesitter - vim async coloring experiment
vim-treesitter
clip-interrogator - Image to prompt with BLIP and CLIP
iswap.nvim - Interactively select and swap function arguments, list elements, and much more. Powered by tree-sitter.
nvim-treesitter-cpp-tools - C++ Helper Snippets Using Treesitter