Blog

Lens Studio can gives one the ability to create some truly amazing augmented reality effects for Snapchat. I’ve found the performance and speed with which these lenses display to be very smooth, and this is due in part to the strict requirements that Snapchat has for the quality of submitted lenses.

However, this performance comes with a price. One of the most challenging things any lens creator faces is fitting everything into the 4mb of space that is allowed.

Continue reading “Tips and Tricks to Keep your Lens Within Lens Studio’s 4mb Limit”

This is the second part in a two-part series. I suggest you read the first part first. Interact with the app via the App link

The goal of the second part of this tutorial series is to deploy the machine learning wine quality prediction web application built in part 1—this time in the cloud.

Continue reading “Deploy a Machine Learning Model as a Web Application (Part 2)”

The joy derived from having artificial intelligence models in production can’t be quantified, especially when users start interacting with the technology. AI products are the end result of iterative processes throughout a larger data science lifecycle.

Continue reading “Deploy a Machine Learning Model as a Web Application (Part 1)”

Entity extraction can be useful when you want to add interactivity to your application based on the context of the text.

For example, if it’s a phone number you can prompt the user to make a call and if it’s an email address you can prompt the user to open the email app. This is achieved by first extracting various entities in the text. In this piece, let’s look at how that can be achieved using Google’s ML Kit.

Continue reading “Entity Extraction with ML Kit”

First things first—

In short, Visual Recognition helps us find meaning in visual content.
We can use Visual Recognition to develop smart applications that analyze the visual content of images or video frames to understand what is happening in a scene.

Continue reading “Visual Recognition in Android Using IBM Watson”

Machine learning and AI are taking mobile application development to a new level. Apps that utilizing machine learning can recognize speech, images, and gestures.

This gives us new and compelling ways to engage and interact with people in the world around us. But how do we integrate machine learning into our mobile apps?

Developing mobile applications that incorporate machine learning has long been a difficult task. But with the help of platforms and dev tools such as Fritz AI, Firebase’s ML, and TensorFlow Lite, it’s getting easier to do so.

Continue reading “Digit Recognizer with Flutter and TensorFlow Lite”

Image and video compression techniques have greatly advanced in recent years. However, most compression techniques still can’t handle the massive growth in media data.

Read on to learn how deep learning (DL) can help solve the challenges of traditional compression frameworks.

Continue reading “How Deep Learning Solves Compression Challenges”