Tips

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.

We look into a Travis CI configuration file in order to test Android projects.

We talk about the different collection structures in Java and how to measure their performance and memory footprint Simple example of performance testing for collection types in java: package org.ea.debugger; import java.lang.management.ManagementFactory; import java.util.*; import java.util.function.IntConsumer; public class CollectionTest { public static void sleep() { try { Thread.sleep(3000); } catch (Exception e) { e.printStackTrace(); }…

We talk about lit-html and different functions available in the library.

We talk about what an accessible app is and how we can improve our testing, both manually and automatic.

We look into how to screenshot in different devices, take coverage metrics and check loading performance.

We look at setting up, running, and setting up deployments on Kubernetes. We talk about running and scaling pods, connecting services and pushing to google cloud.

We use OpenCL to run workloads on GPU and try a simple blur filter.

We compile and look at the code for the Tensorflow lite demo, looking at the key concepts.

We look at connecting up a native library, native source to our Android application.