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playground | blockly | |
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16 | 54 | |
11,674 | 12,103 | |
1.1% | 1.1% | |
0.0 | 9.2 | |
3 months ago | 6 days ago | |
TypeScript | TypeScript | |
Apache License 2.0 | 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
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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.
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Introduction to TensorFlow for Deep Learning
For visualisation and some fun: http://playground.tensorflow.org/
- TensorFlow Playground – Tinker with a NN in the Browser
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Visualization of Common Algorithms
https://seeing-theory.brown.edu/
https://www.3blue1brown.com/
https://playground.tensorflow.org/
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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:
http://playground.tensorflow.org/
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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.
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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
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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.
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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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[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.
blockly
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The Unix Game
Perhaps blockly
https://developers.google.com/blockly
- Google Blockly
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⚧︎ Super Smash Siblings Trans
Unless it would contradict canon, every stage is very bright, highly interactive, full of pre-placed items, and so huge that you can usually run from your NPC opponents and enjoy exploring the stage in peace while they catch up to you. All buildings have Linux computers with actual internet access that allow you to program and print out your own projectiles/books/flags/UNO reverse cards/shinigami eyes/soupcans/cis TERF tears/masks/custom-made programs which can then be inserted into a different computer, but all without tracking any of your browser history; closets that you can enter; bookshelves containing the books mentioned in Masterpieces that you can either read in-game or throw to make random sentences/verses/comics from the book appear; and bathrooms with working mirrors that you can enter but their exact content and whether they're gendered or not depends on the stage.
- Scratch is the world’s largest coding community for children
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(Free) Visual Scripting Game Engine
Google made bockly It works with 5 languages. I think #C PHP and JavaScript. I know JavaScript for sure . But not sure about the others. blockly
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Am I wrong?
And as a corollary, Blockly: https://developers.google.com/blockly
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Ask HN: Best resources to learn Python or JavaScript for children?
https://developers.google.com/blockly/ Blocky with Javascript
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coding
https://developers.google.com/blockly (Block programming, very good with helping learn the logic)
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To be learned before or after Python?
Another block environment Blockly does compile to Javascript, and you can add your own block sets and use it in your existing webapp as a sort of workflow programming tool
- I'm looking for web-based or stand-alone Java blocks editor
What are some alternatives?
clip-interrogator - Image to prompt with BLIP and CLIP
Node RED - Low-code programming for event-driven applications
dspy - DSPy: The framework for programming—not prompting—foundation models
Rete.js - Rete.js is a framework for creating visual interfaces and workflows. It provides out-of-the-box solutions for visualization using various libraries and frameworks, as well as solutions for processing graphs based on dataflow and control flow approaches.
nvim-treesitter - Nvim Treesitter configurations and abstraction layer
react-native - A framework for building native applications using React
pyllama - LLaMA: Open and Efficient Foundation Language Models
Vue.js - This is the repo for Vue 2. For Vue 3, go to https://github.com/vuejs/core
lake.nvim - A simplified ocean color scheme with treesitter support
GrapesJS - Free and Open source Web Builder Framework. Next generation tool for building templates without coding
developer - the first library to let you embed a developer agent in your own app!
imgui-node-editor - Node Editor built using Dear ImGui