Blog

In this blog post, you’ll be learning about how to implement and leverage location data in Android.

Leveraging location data from user devices, you can find nearby shops, cafes, cinemas, hospitals, your time zone, provide location-based suggestions to users, share locations with other users or 3rd parties, reach your destination, and more!

Today, most major applications like Google Maps, Facebook, Uber, Swiggy, etc. are using this feature to provide some of the best services to the users as well.

Continue reading Handling Location Data in Android

To help sift through some of the incredible projects, research, demos, and more in 2019, here’s a look at 17 of the most popular and talked-about projects in machine learning, curated from the r/MachineLearning subreddit. I hope you find something inspiring, educational, or both in this list.

Continue reading Best of Machine Learning in 2019: Reddit Edition

Hyperparameters have inevitably been used by anyone who has practiced machine learning, either in industry, academia, or even self-study. It can be an intimidating term if you’re just starting your dive into machine learning.

And once you’ve figured out how to pronounce the term, the key to understanding hyperparameters is knowing how they differ from parameters.

Continue reading “Tuning Machine Learning Hyperparameters”

In my time as an Android developer, I’ve run into issues with designing app icons for different Android devices and OS versions. Luckily, however, I found a workable solution: to create adaptive icons with Android Studio that work across devices and versions of Android.

Creating an adaptive Icon for Android using Android Studio is relatively easy—but before we jump into an implementation, let’s first take a closer look at what an adaptive icon actually is.

Continue reading Implementing Adaptive Icons in Android Using Android Studio

It’s safe to say that a majority of developers work by consuming REST APIs in their day-to-day tasks. And this is not at all surprising as REST is amazing architecture.

But since the development landscape and the technologies within that landscape are constantly changing, developers need to keep themselves up-to-date with the latest and greatest, especially when it comes to optimizing development time, cost, speed, and more. And to achieve this, GraphQL enters in the picture.

Continue reading GraphQL with Android

In case you were wondering, no — Fastlane doesn’t have an enterprise offering. It’s always been (and I hope will continue to be) an open-source product.

Fastlane is a collection of tools that help you automate all aspects of mobile development, such as creating new app IDs in the developer portal and managing provisioning profiles; building, testing and packaging apps; and distributing apps to the App Store.

Continue reading Working with Fastlane on iOS in an Enterprise Environment

This tutorial is a quick guide on how to integrate Facebook login with Firebase while developing with React Native. By using Firebase and Facebook login, you’ll be able to understand how to use and integrate Firebase properly, as well as implement Facebook authentication along with login. This process will also help developers learn a lot about Firebase, which can be used as lightweight and easy-to-configure backend.

Continue reading Implementing Facebook login on Android with React Native and Firebase

Mercari is a popular shopping app in Japan that has been using AutoML Vision (Google’s AutoML solution) for classifying images. According to Mercari, they’ve been “developing their own ML model that suggests a brand name from 12 major brands in the photo uploading user interface.”

Continue reading AutoML: The Next Wave of Machine Learning