@@ -21,34 +21,33 @@ Documentation site: [www.scikitjs.org](https://www.scikitjs.org)
 For use with modern bundlers in a frontend application, simply
 
 ```bash
+npm i @tensorflow/tfjs
 npm i scikitjs
 ```
 
-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 * as sk from 'scikitjs'
+sk.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 @tensorflow/tfjs-node
 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 * as sk from 'scikitjs'
+sk.setBackend(tf)
 ```
 
 ### Script src
@@ -57,16 +56,21 @@ 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"
+  sk.setBackend(tf)
+
+  // or alternatively you can pull the bundle from unpkg 
+  // import * as sk from "https://unpkg.com/scikitjs/dist/web index.min.js"
 </script>
 ```
 
 ## Simple Example
 
 ```js
-import { LinearRegression } from 'scikitjs'
+import * as tf from '@tensorflow/tfjs-node'
+import { setBackend, LinearRegression } from 'scikitjs'
+setBackend(tf)
 
 const lr = new LinearRegression({ fitIntercept: false })
 const X = [[1], [2]] // 2D Matrix with a single column vector
@@ -124,7 +128,9 @@ Turns into
 #### JavaScript
 
 ```js
-import { LinearRegression } from 'scikitjs'
+import * as tf from '@tensorflow/tfjs-node'
+import { setBackend, LinearRegression } from 'scikitjs'
+setBackend(tf)
 
 let X = [[1], [2]]
 let y = [10, 20]
@@ -154,7 +160,9 @@ Turns into
 #### JavaScript
 
 ```js
-import { LinearRegression } from 'scikitjs'
+import * as tf from '@tensorflow/tfjs-node'
+import { setBackend, LinearRegression } from 'scikitjs'
+setBackend(tf)
 
 let X = [[1], [2]]
 let y = [10, 20]
@@ -189,7 +197,9 @@ Turns into
 #### JavaScript
 
 ```js
-import { LogisticRegression } from 'scikitjs'
+import * as tf from '@tensorflow/tfjs-node'
+import { setBackend, LogisticRegression } from 'scikitjs'
+setBackend(tf)
 
 let X = [[1], [-1]]
 let y = [1, 0]