Category: Articles

People are passionate about pizza. Deep dish, thin crust, traditional pan, flatbread — and those are just styles of crust, to say nothing of topping preferences. Pineapple? Anchovies??

With such a wide variety of styles and preferences to swear by, it’s important for pizza lovers to have an authoritative source for honest and legitimate reviews — and the chance to share their love of pizza with others.

Continue reading “One Bite pizza reviews: Building community trust with mobile machine learning”

WebViews in Android are often seen as a lazy programmer’s tool—Don’t have enough time to build a particular screen for your app? Just use a WebView to display a page from your website instead. Users won’t be able to tell the difference…right?

Jokes aside, while you’ll often hear other developers discouraging the use of WebViews, they’re often necessary. For example, if you want to make a transaction with your bank or credit card, that transaction screen is a WebView.

Custom login screen for apps where security is a concern is often a WebView instead of a native widget. Google Mobile Ads (or Admob) also uses a WebView to display Banner and Interstitial ads on your app.

Continue reading “Working with WebViews in Android”

If you’re looking for help in easily adding machine learning to your Android apps, you’ve come to the right place. In this article, we’ll learn how to get started, implementing a task known as text recognition.

Continue reading “Recognize Text in Images on Android with Firebase’s ML Kit”

I’ve always thought of community as something akin to a party. A thing that forms largely by happenstance, where the people involved are connected through discrete and clear purposes: Socializing, relaxing after a long work week, meeting new people.

So when I found myself in the role of building the Heartbeat community, I initially struggled to see a bigger picture. I had the vague sense that the main priority should be centered on putting the needs and desires of community members first—much in the same way I’d want to be a good host at a party.

Continue reading “Building the Heartbeat Community”

There exist a plethora of articles on quantization, but they generally cover only the surface level theory or provide a simple overview. In this article, I’ll explain how quantization is actually implemented by deep learning frameworks.

Before getting into quantization, it’s good to understand the basic difference between two key concepts: float (floating-point) and int (fixed-point).

Continue reading “Quantization Arithmetic”

A Non-Developer Building Mobile ML?

I’m by no means a developer, engineer, or coder of any kind. Though I do read a lot of tutorials that include code implementations, and occasionally peruse repos to explore what folks are building, the most I’ve ever done is add some CSS style elements to a button within an HTML file.

So on the surface, the idea of me being able to build a cross-platform, mobile-ready machine learning model is kind of absurd.

Continue reading “End-to-End Mobile Machine Learning with Fritz AI Studio: A Non-Developer’s Journey”

Developers using Fritz AI can now track the body positions of people in images and video with Pose Estimation.

Continue reading “Pose Estimation on Android”

Deploying machine learning-based Android apps is gaining prominence and momentum with frameworks like TensorFlow Lite, and there are quite a few articles that describe how to develop mobile apps for computer vision tasks like text classification and image classification.

But there’s very much less that exists about working with audio-based ML tasks in mobile apps, and this blog is meant to address that gap — specifically, I’ll describe the steps and code required to perform audio classification in Android apps.

Continue reading “Audio Classification in an Android App with TensorFlow Lite”

Google’s Colab is a truly innovative product for machine learning. It enables machine engineers to run Notebooks and easily share them with colleagues. Another key advantage is access to GPUs and TPUs.

In this piece, we’ll highlight some of the tips and tricks mentioned during this year’s TF summit. Specifically, these tips will help you in getting the best out of Google’s Colab.

Continue reading “Top 10 Tricks for TensorFlow and Google Colab Users”