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Nothing frustrates me more than filling out a long form on my phone. The keyboard is too small and questions always feel redundant. Streamlining UX with helpful suggestions and auto-completion is a great way to reduce friction, increase conversion, and make your app feel more fluid.

Amazon realized this early, resulting in their infamous “1-click” patent. Google reports that over 12% of all emails sent are composed via their single click Smart Reply option. In this tutorial, we’ll use Apple’s Create ML tool to train our own machine learning model to anticipate a user’s intentions, automatically complete a form, and save them a click in the process.

Continue reading “Using Create ML on iOS to auto-complete forms”

By now, you are probably familiar with the concept of “smart reply” features. In many messaging applications nowadays, you’ll see a list of suggested replies when you receive a message. And this makes it easier to respond without thinking about what you’re going to say—especially when the reply is obvious.

You can easily add Smart Reply to your mobile apps. like chat-app, Reviews, with the help of Google’s API, via its on-device machine learning framework ML Kit, which allows you to easily add this capability to your projects.

Continue reading “On-Device Smart Replies on Android using Google’s ML Kit”

It’s really important to work and develop your code in a trusted and isolated environment—an environment that’s easy to set up and lets you start working on your project right away.

Continue reading “How to Create a Reliable Python Environment Using Docker: Tips for Data Science”

While writing an article or creating a YouTube video, have you ever encountered a problem where you want to use a certain image, but its resolution is too low and unclear, so you have to use a less suitable but more crisp image?

Machine learning-based super resolution might be the solution to this problem.

In its essence, super resolution in machine learning refers to models that take a low-resolution image as input and produce an upscaled, clear, high-resolution image as the output.

Continue reading “Introduction to Super-Resolution Machine Learning Models”

Swarm intelligence (SI) is the collective behavior of decentralized, self-organized systems, whether natural or artificial. It’s an emerging field of biologically-inspired artificial intelligence based on the behavioral models of social insects such as ants, bees, wasps, termites, etc.

All swarm intelligence agents have two properties in common:

Continue reading “Artificial Bee Colony Algorithm”