ml5js · shiffman · Feb 28, 2018 · Feb 23, 2018 · Feb 23, 2018 · Feb 27, 2018
diff --git a/docs/api-Getting-Started.md b/docs/api-Getting-Started.md
@@ -30,4 +30,53 @@ That's all!
 
 ## Creating a simple image recognition example
 
-TODO
+Make a new `index.html` and paste in the below code. Make sure the first `<script>` tag is pointing to a copy of [ml5.min.js](https://github.com/ITPNYU/ml5/tree/master/dist). Open it in a web browser and after a couple seconds of computation you should see something like this:
+
+<img src="assets/img/getting-started.png">
+
+This demo needs only ML5 to run. When the HTML is parsed by the browser, it loads the `<img>` tag, at which point it gets an image from Imgur using a cross-origin request. When the image is loaded, `onImageReady()` is called, and it resizes the image to something small enough that it runs quickly, then asks ImageNet for its best prediction as to what the image is, along with its confidence level. Then it prints the result to the specified DOM elements.
+
+```html
+<!DOCTYPE html>
+<html>
+  <head>
+    <meta charset=utf-8>
+    <title>Simple ML5.js Example</title>
+    <script src="libraries/ml5.min.js"></script>
+    <script>
+      // Initialize the imageNet method with the SqueezeNet model.
+      let imagenet = new ml5.ImageNet('SqueezeNet');
+
+      function onImageReady() {
+        // Get the image element from the page
+        let img = document.getElementById('image');
+
+        // Force the image into a smaller size/ratio for the classifier
+        img.width = 227;
+        img.height = 227;
+
+        // Get a prediction for that image
+        imagenet.predict(img, 10, gotResult);
+      }
+
+      // When we get the results
+      function gotResult(results) {
+        // The results are in an array ordered by probability.
+        console.log(results);
+        document.getElementById('result').innerText = results[0].label;
+        document.getElementById('probability').innerText = results[0].probability.toPrecision(2);
+      }
+    </script>
+  </head>
+  <body>
+
+  <!-- This is the image we want to use. We can change the src later in code. We set crossOrigin to anonymous because imgur will respect that and send CORS headers. Not needed if you're loading an image from your own domain. -->
+
+  <h1>Simple Image Classification Example</h1>
+  <img id="image" crossOrigin="anonymous" src="https://i.imgur.com/wxrLX68.jpg" onload="onImageReady()">
+
+  <p>I guess this is a <span id="result">...</span>. My confidence is <span id="probability">...</span></p>
+
+  </body>
+</html>
+```
diff --git a/docs/assets/img/getting-started.png b/docs/assets/img/getting-started.png