We look into training your model locally on windows and other platforms.

Looking into the configuration file and talk about what the different parameters mean

We build TFRecord file using java and talking about how to easily label your images for object detection.

We look at an example from ml5js to load images and predict them

We look at a regular expression to parse a URL in detail so we can reason about regex.

We use Toco to convert our cats and dogs model to Tensorflow lite and run it on an Android device.

We look at creating self signed certificates and get them working with your docker image. We talk about different encryption and authentication algorithms and other configuration options.

We look into lighthouse testing on Travis CI and SauceLabs.

I talk about my experience at a hackathon last weekend.

We set up a simple Polymer 3.0 element and then transform it to use lit-html

We look into how to build docker images for performance. Talk about the compromises between speed and size.

We look into how to create TFRecords to and handle images from a custom dataset. Later we load these records into a model and do some predictions.