For this tutorial, you need a basic knowledge of React Native and some familiarity with Expo. You’ll also need the Expo client installed on your mobile device or a compatible simulator installed on your computer Instructions on how to do this can be found here.
Continue reading Handling responsive layouts in React Native apps
We’ve seen a bunch of great use cases for on-device ML, but sometimes it’s easy for us to get a bit lost in the weeds. For many mobile developers, the idea of machine learning can sound scary—math, a steep learning curve, and questions about the need for machine learning features in the first place.
Mobile apps are made of screens that can vary in number depending on the app you’re developing. Handling user navigation can be tricky to learn and implement in mobile apps, but with dedicated open source libraries like react-navigation, the process becomes a lot easier.
React Navigation is a common library among React Native developers. It’s built with JavaScript, and you can create React components and apply any navigation pattern. On the device, it’ll provide a natural look and feel.
Continue reading How Authentication Flow works in React Native apps using React Navigation 4.x
Photography has been Apple’s central focus since the inception of the iPhone. Over the years, they’ve released amazing new features that make the world a difficult place to live in without an iPhone. Users are able to capture better and better photos, thanks to state-of-the-art image intelligence features Apple has steadily added.
Specifically, Apple has been investing heavily in the field of computer vision, rolling out major updates every year through its Vision framework, which was released in 2017.
Continue reading Scanning Credit Cards with Computer Vision on iOS
Nowadays, one issue that flies under the radar for Android developers is app security. Although the Android OS possesses a layer of security that’s sufficient most of the time, it can be enhanced by adding an extra layer of security using some advanced mechanisms and features.
Today’s article is going to cover some of these best practices and mechanisms to better secure your apps.
Continue reading Securing Network and Inter-App Communications on Android
Generative adversarial networks (GANs) are among the more significant advancements in deep learning in recent years. Previously, we used machine learning and deep learning techniques with a considerable amount of data to build a model to understand data by classifying them. But now, with GANs, we use an algorithm that generates data for us.
Two of the most commonly used and efficient generative models are Variational Autoencoders (VAE) and Generative Adversarial Networks (GAN).
Continue reading Generative Adversarial Networks (GANs) for Mobile Devices
At some point, you might have asked yourself, What are the origins of parameters for artificial neural networks? What is the purpose of the weight? What if no bias is used?
In this tutorial, we set out to answer those questions by working from the most simple artificial neural network (ANN), to something much more complex. Let’s start by building a machine learning model with no parameters—which is Y=X.
Continue reading From Y=X to Building a Complete Artificial Neural Network
In the landscape of new technologies that are capable of revolutionizing our daily lives, few are as tantalizing as facial recognition technologies. With all the recent controversy around Clearview AI, people are paying more and more attention to the technology, and they’re also eager to understand the how the tech works, and it’s limitations. This article won’t cover this ethical issue, but I’ll try my hand at explaining some facial recognition and detection techniques.
Continue reading Face Recognition and Detection on iOS Using Native Swift Code, Core ML, and ARKit
In a recent blog post, Facebook announced React Native version 0.62, and one of the top features of this release was a default integration of Flipper.
Flipper is an open source mobile debugging platform backed by Facebook. It is widely used by Android & iOS developers. Flipper’s simple and intuitive interface helps developers to visualise, inspect & control apps. It aims to be the number one companion for mobile app development.
Deep learning has seen tremendous progress over the past few years. This is largely due to the emergence of deep learning frameworks such as PyTorch and TensorFlow, which have greatly simplified even the most sophisticated research.
With smartphones having become the devices we use the most, the next wave of innovation is going to center on how we can leverage these rapid advances in deep learning to enhance our smartphone experiences. AI-powered mobile applications will become (and already are) smart enough to understand us and help us perform tasks via visual perception, language understanding, and voice recognition, even when not connected to the internet.
Continue reading PyTorch Mobile: Image classification on Android
