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Tangram is an automated machine learning framework designed for programmers.
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- Run `tangram train` to train a model from a CSV file on the command line.
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- Make predictions with libraries for [Elixir](https://hex.pm/packages/tangram), [Go](https://pkg.go.dev/github.com/tangramxyz/tangram-go), [Node.js](https://www.npmjs.com/package/@tangramxyz/tangram-node), [Python](https://pypi.org/project/tangram), [Ruby](https://rubygems.org/gems/tangram), and [Rust](lib.rs/tangram).
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- Make predictions with libraries for [Elixir](https://hex.pm/packages/tangram), [Go](https://pkg.go.dev/github.com/tangramxyz/tangram-go), [JavaScript](https://www.npmjs.com/package/@tangramxyz/tangram), [Python](https://pypi.org/project/tangram), [Ruby](https://rubygems.org/gems/tangram), and [Rust](lib.rs/tangram).
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- Run `tangram app` to learn more about your models and monitor them in production.
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### Install
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### Predict
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Make predictions with libraries for [Elixir](https://hex.pm/packages/tangram), [Go](https://pkg.go.dev/github.com/tangramxyz/tangram-go), [Node.js](https://www.npmjs.com/package/@tangramxyz/tangram-node), [Python](https://pypi.org/project/tangram), [Ruby](https://rubygems.org/gems/tangram), and [Rust](https://lib.rs/tangram).
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Make predictions with libraries for [Elixir](https://hex.pm/packages/tangram), [Go](https://pkg.go.dev/github.com/tangramxyz/tangram-go), [JavaScript](https://www.npmjs.com/package/@tangramxyz/tangram), [Python](https://pypi.org/project/tangram), [Ruby](https://rubygems.org/gems/tangram), and [Rust](https://lib.rs/tangram).
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```javascript
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let tangram =require("@tangramxyz/tangram-node");
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let tangram =require("@tangramxyz/tangram")
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let model =newtangram.Model("./heart_disease.tangram");
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let model =newtangram.Model("./heart_disease.tangram")
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let input = {
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age:63,
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gender:"male",
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// ...
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};
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}
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let output =model.predictSync(input);
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console.log(output);
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let output =model.predict(input)
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console.log(output)
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```
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```javascript
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input,
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options,
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output,
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});
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})
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```
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Later on, if you find out the true value for a prediction, call `logTrueValue`.
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