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Machine Learning with JavaScript. Fast and Simple. :rocket:

License: MIT License

JavaScript 100.00%

machine-learning-with-js's Introduction

Machine Learning with JavaScript 🚀

You don't need ~~Python~~ to train your own models and perform Machine Learning.

This repository is linked to a series I have been writing about on Medium.com, regarding ML in JS.

Machine Learning with Javascript : Part 1

Repository Info

The repository is organized as follows:

Linear Regression | linear-regression
k Nearest Neighbors | knn

Get started

Clone this repo, or fork it and clone your own copy.
Run npm install or yarn inside the repository to download the required node_modules.

That's it.

Run the following command to run your model.

$ node index.js

Tweak certain things inside index.js and run again. Awesome, eh? 🎉

Contributing

If you have an idea for this repository, or if you want to contribute to this series, please open a Pull Request. I await your shenanigans. 😆

machine-learning-with-js's People

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machine-learning-with-js's Issues

Update the tutorial ?

Hello,

Thx for your tuto on Hackernoon. However the code isn't up to date. You use "const knn = new KNN()", and it doesn't work with the current version of ml-knn,
Can you update the code of the tutorial please ?

Thx in advance,

Jajoe

knn example needs to require csvtojson/v1 instead of csvtojson

I just wanted to let you know that I had to change require(csvtojson) to require(csvtojson/v1) in order to get the knn example working, otherwise the data array was not filled.

y returns as NaN even after fixing capitalization for radio and sales

Y always returns 'NaN' in the console

No matter how long you try to train it with new values, it never starts doing anything

it can’t find the row values

machine-learning-with-js/linear-regression/index.js

Line 49 in c25d65b

X.push(f(row.Radio));

should be:

csvData.forEach((row) => {
X.push(f(row.radio));
y.push(f(row.sales));
});

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