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)”
About a year and a half ago, I wrote a blog post titled “What Is Explainable Artificial Intelligence and Is It Needed?” In the post, I discussed how transparent and explainable the decision-making process of humans is.
On the other hand, I gave examples of the balance between the performance of AI applications and the decrease in explainability.
Continue reading “Explainable, Responsible, and Trustworthy Artificial Intelligence”
With advances in camera quality, image fidelity, and neural network research focused on solving image- and video-based challenges, computer vision continues to capture the attention and imaginations of machine learning researchers and practitioners.
But computer vision is an incredibly broad umbrella term that encompasses an array of specific tasks and challenges, and the field continues to expand.
Continue reading “Machine Learning for Computer Vision: Foundations and Use Cases”
Splash screens are as old as mobile phones themselves, as you can see from this picture of an old school Nokia phone:
Continue reading “Splash Screens in Android — Implementing them Correctly”
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.
First things first—
What is Visual Recognition? And where can it be used??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”
With the advent of neural networks, machine learning has gained immense popularity, and companies in just about every industry have started to apply some form of this vast technology to increase efficiency, improve throughput, or enhance customer experiences.
Artificial intelligence as a field has seen major breakthroughs in many areas within the past decade. With so many industries jumping towards automation and trying to apply AI to enhance customer experiences, it’s started to create a bigger impact in our day-to-day lives.
Being used on such a large and varied scale, it has recently come to light that these methods come with their own problems.
