At WWDC 2020, Apple introduced a bunch of great new updates to SwiftUI to make it even easier for developers to write apps for Apple platforms. In this tutorial, you’ll learn how to use those new features to make your app work on both iOS and macOS. By the end of this tutorial you will have created a fully functional HackerNews reader.
Category: Articles
Ditching Xcode’s ▶️ button
Articles
If you’re tired of building and running your iOS apps via Xcode’s ▶️ button, let’s explore an exciting way to build and run your apps without touching the ▶️ button (ever again).
This is a four-step process.
Xcode comes with a number of command line tools. These tools are capable of performing pretty much every thing you can do via Xcode’s UI. While you need a human to point and click certain buttons in Xcode to make it work, these command line tools can help automate the whole process of building and running your project. Powerful, right?
Sentiment Analysis of Speech Using PyDub and SpeechRecognition in Python
Articles
The ability of a machine or program to identify spoken words and transcribe them to readable text is called speech recognition (speech-to-text). In this tutorial, I will be walking you through analyzing speech data and converting them to a useful text for sentiment analysis using Pydub and SpeechRecognition library in Python.
Sentiment analysis is the use of natural language to classify the opinion of people. It helps to classify words (written or spoken) into positive, negative, or neutral depending on the use case. The sentiment analyzed can help identify the pattern of a product; it helps to know what the users are saying and take the necessary steps to mitigate any problems.
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End-to-End Machine Learning in JavaScript using Danfo.js and TensorFlow.js (part 1)
ArticlesMachine learning (ML) is arguably the most sought after skill in the fields of data and computer science. ML related projects and problems can be done using any programming language.
Developers have been led to believe that, to build and train an ML model, they are restricted to using a select few programming languages— Python, R and Java often top the list.
Debugging machine learning models
Articles
If our data isn’t good enough, there’s no machine learning tool, platform, or framework that exists that will work well—no matter how good the algorithm is.
So while debugging machine learning models, we also need to make sure our input data is prepared properly. For example the input data may not be a valid data type for a particular feature. Like in case of gender the allowed values are M or F, while the input data may contain other letter values for this feature.
Exploring SnapML: A Technical Overview
Articles
For years now, Snapchat has been at the forefront of mobile machine learning — their popular Lenses, which often combine on-device ML models with augmented reality, have become shining examples of the power and flexibility of on-device machine learning.
Given our respect and admiration for Snap’s work in this area, our team was thrilled to hear about the recent release of SnapML, Snap’s new ML framework inside their development platform Lens Studio (released with 3.0).
Exploring the new ML Kit features on iOS using Swift
Articles
Last year, at I/O 2018, Google announced a brand new SDK available for developers: ML Kit. It’s no surprise that Google’s advances in machine learning are miles ahead of what any other company is aiming for. Through this SDK, Google was hoping to help mobile developers bring machine learning to their apps with simple, concise code. As part of the Firebase ecosystem, ML Kit allows developers to implement ML functionality with just a few lines of code; everything from vision to natural language to custom models.
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Deploying and Hosting a Machine Learning Model Using Flask, Heroku and Gunicorn
Articles
One thing I’ve observed in many data science tutorials when it comes to modeling, is that once a certain performance threshold is achieved on test data, rarely is the model deployed/pushed to production—and it’s a common case in the industry more broadly.
This tutorial aims to take modeling a step further by building a REST API and deploying the model into production. In addition to the REST API, we’re building a simple web application that predicts whether a piece of text belongs to any of these classes: atheism, computer graphics, medical science, Christianity, or politics.
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How Snapchat Lenses affect TikTok trends — and why Lens Creators are so important
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You must’ve heard about “Vin Rouge” by @Nikhilodeon12 by now. The newly-verified Snap Star Nikhil created this lens, sparking the viral “Silhouette” challenge on TikTok. That’s right, TikTok.
The platform filled with its own filters, special effects, and AR tools. How did a Snapchat Lens end up over there?
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Heatmaps and CNNs Using Fast.ai
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In my article on lessons from my first deep learning hackathon, I introduced heatmaps. I mentioned that they highlight the regions in an image that the CNN focuses on while trying to make a prediction, and that it would be interesting to learn how they’re generated. Well, I finally know how. Let’s first go back and see what they look like.