Apple’s WWDC 2020 (digital-only) event kickstarted with a bang. There were a lot of new surprises from the world of SwiftUI, ARKit, PencilKit, Create ML, and Core ML. But the one that stood out for me was computer vision.
Apple’s Vision framework got bolstered with a bunch of exciting new APIs that perform some complex and critical computer vision algorithms in a fairly straightforward way.
Continue reading SwiftUI + Vision Contour Request — Coin Detection in iOS
As the spread of COVID 19 continues, communities are told to reduce close contact between individuals. This is called Social Distancing, as it is a necessary and effective way to slow down the spread of the virus. As a data science student, I came with a solution to identify whether people actually follow the social distancing protocol of staying at least 6 feet from each other.
Continue reading Social Distance Detector with Python, YOLOv4, Darknet, and OpenCV
Data pre-processing is a necessary step before any neural network can successfully ingest and analyze that data. The methods used to do this pre-processing are critical to the network’s performance.
Traditional data pre-processing methods include mean subtraction, normalization, and whitening, which have been around a long time—well before batch normalization came into the picture, which is what we’ll focus on in this post. To start, let’s define these pre-processing methods.
In this post, we’ll have explore the fundamentals of ensemble learning. Specifically, we’ll discuss techniques like bagging, boosting, and stacking in detail and take a brief look at various foundational algorithms that adopt these techniques.
Without further ado, let’s get started!
This article presents techniques for improving classification accuracy by aggregating various classifiers in different ways. These techniques are known as the ensemble methods.
Revamp that old security camera you have in your backyard — the one that doesn’t even record images! Security systems too costly? Get working on build your own with Twilio and OpenCV !
One of the largest boons of technology has been how, with time, advanced camera and surveillance systems have become so widely accessible. Twilio today has democratized communications channels like voice, text, chat, video, and email by virtualizing the world’s comms infrastructure through APIs that are simple enough for any developer to use, yet robust enough to power the world’s most demanding applications.
Continue reading Remote face detection system with OpenCV and Twilio
This post gives an overview of the different techniques for how to handle categorical variable encoding—i.e. permanently replacing category strings with numerical representations.
Continue reading “Hands-on with Feature Engineering Techniques: Encoding Categorical Variables”
Today, we’re going to be building a RESTFUL API that takes in an image and make predictions using a TensorFlow MobileNet pre-trained model.
TensorFlow.js has many pre-trained models that can be used in projects out of the box. This saves developers the task of training a model from scratch. Here we’re going to explore the MobileNet pre-trained architecture
Genetic Algorithms (GAs) are a subset of Evolutionary Algorithms, which use mechanisms inspired by nature such as mutation, evolution, reproduction, etc. In spite of using advanced math, these algorithms work on principles which are derived from nature. Growth of an organism in its environment and its interaction with other beings in that environment can be modeled with simple mathematical expressions.
Continue reading Hyperparameter Optimization With Genetic Algorithms In Kotlin
Machine learning tech is being integrated into mobile applications more and more today. Its integration helps optimize overall performance and can add significant functionality to an app’s experience. And over time, ML models can learn and improve from user interactions, making these experiences super intuitive and intelligent.
Here, we’re going to continue working with this technology in the Flutter ecosystem. Check out my previous post on ML in Flutter for more:
Continue reading Emoji Classification with Flutter and TensorFlow Lite
Camera effects have become a very normal part of daily social media or really any camera experience on the internet nowadays. With the whole pandemic situation, video calls have become way more popular, and to add a bit of artistic fun to the plain camera outputs, a lot of apps have integrated AR filters that overlay the face or change your background to hide that messy room.
Continue reading Creating Instagram and Facebook AR Filters with Spark AR Studio (Part 4)
