playground
nvim-lua-guide
Our great sponsors
playground | nvim-lua-guide | |
---|---|---|
16 | 152 | |
11,674 | 4,992 | |
1.1% | - | |
0.0 | 6.3 | |
3 months ago | over 1 year ago | |
TypeScript | sed | |
Apache License 2.0 | - |
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
-
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.
-
Introduction to TensorFlow for Deep Learning
For visualisation and some fun: http://playground.tensorflow.org/
- TensorFlow Playground – Tinker with a NN in the Browser
-
Visualization of Common Algorithms
https://seeing-theory.brown.edu/
https://www.3blue1brown.com/
https://playground.tensorflow.org/
-
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:
http://playground.tensorflow.org/
-
Let's revolutionize the CPU together!
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.
-
Curious about Inputs for neural network
I don’t know much experimenting you’ve done, but many repeated small scale experiments might give you a better intuition at least. I highly recommend this online tool for playing with different environmental variables, even if you’re comfortable coding up your own experiments: http://playground.tensorflow.org
-
Intel Announces Aurora genAI, Generative AI Model With 1 Trillion Parameters
Even if you can’t code, play around with this tool: https://playground.tensorflow.org — you can adjust the shape of the NN and watch how well it classifies the data. Model size obviously matters.
-
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.
-
[Discussion] Questions about linear regression, polynomial features and multilayer NN.
Well there is no point of using a multilayer linear neural network, because a cascade of linear transformations can be reduced to a single linear transformation. So you can only approximate linear functions. However if you have prior knowledge about the non linearity of your data lets say you know that it is a linear combination of polynomials up to certain degree, you can expand your input space by explicitly making non linear transformation. For instance a 1D linear regression can be modeled by 2 input neurons and 1 output neuron where the activation of the output is the identity. The input neuron x0 will take a constant input namely 1 and the second input neuron x1 will takes your data x. The output neuron will be y=w_0 * 1+w_1 *x which is equal to y=w_0 +w_1 * x. Let us say that your data follows a polynomial form, the idea is to add input neurons and expand your input to for instance X=[1 x x2] in this case you have 3 input neurons where the third is an explict non linear form of the input so y=w_0 + w_1 x +w_2 x2. The general idea is to find a space where the problem becomes linear. In real life example these spaces are non trivial the power of neural network is that they can find by optimization such space without explicitly encoding these non linearities. Try playing around with https://playground.tensorflow.org/ you can get an intuition about your question.
nvim-lua-guide
-
Any guide to start writing plugins?
Nvim Lua guide
- I'm fairly new to Neovim, and I want to configure my neovim setup.
-
Advice/Resources for creating/debugging a Neovim Plugin?
My main struggles beyond a simple problem are just the inability to find a way to easily debug things and the general process for setting up a plugin. I mostly work with Python/Jupyter, some C and Lua/Bash scripts, and usually you can either write tests/print debug for smaller scale things or get some stack trace if you have an error. With Neovim development, it just feels like there's nothing more besides update plugin, try on neovim, fail, bash head against wall, and repeat, and that doesn't quite seem efficient or correct - I'm sure there's something out there that should make the process easier. I tried looking online but I haven't found many that really fit my needs (most of the resources here seem more targeted towards creating your own init.lua, and Luadev plugin's commands are all broken (:Luadev-RunLine and any other command keeps telling me I got some trailing space). I'm really just looking to see how to make a snippet library, but there doesn't seem to be much that helps me. If someone could let me know how they debug their plugin or point me to any external resources, please let me know!
-
[help] use neovim to edit files at remote - server?
I have no guidance for the first point. For the second, checkout the neovim lua guide or : lua-guide
- Is there a vim/neovim equivalent to something like "Mastering Emacs"?
- [Neovim] Puis-je obtenir un guide sur la façon d’installer Packer pour les nuls absolus ?
- New to NeoVim, looking to learn
- Where to learn about Neovim and it's plugins? (Deeply)
-
Where would be a good place to start trying to learn lua with no previous programming experience. Trying to learn it as it’s the main language used in a project I’m apart of and want to help out
A quick google search turned up this codeacademy class on learning to program in Javascript. I didn't vet the whole thing, but it appears to assume you know nothing, which is what you need. If you go through that, you can then consume one of the resources that /u/luascriptdev post to equate that back to Lua. Again, the concepts translate.
- how to understand lua config
What are some alternatives?
clip-interrogator - Image to prompt with BLIP and CLIP
kickstart.nvim - A launch point for your personal nvim configuration
dspy - DSPy: The framework for programming—not prompting—foundation models
packer.nvim - A use-package inspired plugin manager for Neovim. Uses native packages, supports Luarocks dependencies, written in Lua, allows for expressive config
nvim-treesitter - Nvim Treesitter configurations and abstraction layer
vim-test - Run your tests at the speed of thought
pyllama - LLaMA: Open and Efficient Foundation Language Models
plenary.nvim - plenary: full; complete; entire; absolute; unqualified. All the lua functions I don't want to write twice.
lake.nvim - A simplified ocean color scheme with treesitter support
tree-sitter-svelte - Tree sitter grammar for Svelte
developer - the first library to let you embed a developer agent in your own app!
which-key.nvim - 💥 Create key bindings that stick. WhichKey is a lua plugin for Neovim 0.5 that displays a popup with possible keybindings of the command you started typing.