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May 19, 2022
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Updated the README #227

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41 changes: 24 additions & 17 deletions README.md
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Original file line number Diff line number Diff line change
Expand Up @@ -24,15 +24,18 @@ For use with modern bundlers in a frontend application, simply
npm i scikitjs
```

Usage is similar to other js libraries.
Usage is similar to other js libraries. We depend on the tensorflow library in order to make our calculations fast, but we don't ship it in our bundle. We use it as a peer dependency. General usage is as follows.

```js
import { LinearRegression } from 'scikitjs'
import * as tf from '@tensorflow/tfjs'
import { LinearRegression, setBackend } from 'scikitjs'
setBackend(tf)
```

This allows us to build a library that can be used in Deno, Node, and the browser with the same configuration.
### Backend Users

For Node.js users who wish to bind to the Tensorflow C++ library, simply
For Node.js users who wish to bind to the Tensorflow C++ library, simply import the tensorflow C++ version, and use that as the tf library

```bash
npm i scikitjs
Expand All @@ -41,14 +44,9 @@ npm i scikitjs
But then import the node bindings

```js
import { LinearRegression } from 'scikitjs/node'
```

The `scikitjs/node` path uses the new "exports" feature of node (which is available in node v13.3+).
If you are using an older version of node, simply pass in the path to the cjs build

```js
import { LinearRegression } from 'scikitjs/dist/cjs/index.js'
import * as tf from '@tensorflow/tfjs-node'
import { LinearRegression, setBackend } from 'scikitjs'
setBackend(tf)
```

### Script src
Expand All @@ -57,16 +55,19 @@ For those that wish to use script src tags, simply

```html
<script type="module">
import * as tf from 'https://cdn.skypack.dev/@tensorflow/tfjs'
import * as sk from 'https://cdn.skypack.dev/scikitjs'
// or alternatively you can pull the bundle from unpkg
import * as sk from "https://unpkg.com/scikitjs/dist/web/index.min.js"
// or alternatively you can pull the bundle from unpkg >>> import * as sk from "https://unpkg.com/scikitjs/dist/web index.min.js"
sk.setBackend(tf)
</script>
```

## Simple Example

```js
import { LinearRegression } from 'scikitjs'
import * as tf from '@tensorflow/tfjs-node'
import { LinearRegression, setBackend } from 'scikitjs'
setBackend(tf)

const lr = new LinearRegression({ fitIntercept: false })
const X = [[1], [2]] // 2D Matrix with a single column vector
Expand Down Expand Up @@ -124,7 +125,9 @@ Turns into
#### JavaScript

```js
import { LinearRegression } from 'scikitjs'
import * as tf from '@tensorflow/tfjs-node'
import { LinearRegression, setBackend } from 'scikitjs'
setBackend(tf)

let X = [[1], [2]]
let y = [10, 20]
Expand Down Expand Up @@ -154,7 +157,9 @@ Turns into
#### JavaScript

```js
import { LinearRegression } from 'scikitjs'
import * as tf from '@tensorflow/tfjs-node'
import { LinearRegression, setBackend } from 'scikitjs'
setBackend(tf)

let X = [[1], [2]]
let y = [10, 20]
Expand Down Expand Up @@ -189,7 +194,9 @@ Turns into
#### JavaScript

```js
import { LogisticRegression } from 'scikitjs'
import * as tf from '@tensorflow/tfjs-node'
import { LogisticRegression, setBackend } from 'scikitjs'
setBackend(tf)

let X = [[1], [-1]]
let y = [1, 0]
Expand Down