Introduction to Python Magic Methods in Python Classes

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Python magic methods are also known as dunder methods or special methods. But why such dramatic names? They’re used to overwrite or emulate the behavior of built-in functions.

They’re also easy to recognize, as they follow a particular pattern: They have double underscores as prefixes and suffixes. Hence, the name dunder means Double Underscore. They’re referred to as special methods because they add “magic” to your python classes. Common examples are __init__(), __str__(), __call__(), etc. A magic method is generally used to override operations.

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Hands-on with Feature Engineering Techniques: Handling Outliers

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This post is a part of a series about feature engineering techniques for machine learning with Python.

You can check out the rest of the articles:

Welcome back! In this post of our series on feature engineering, we’re going to focus on another common issue in most datasets—outliers. Here, we’ll examine what an outlier is and the different methods to handle them, alongside some code snippets. Let’s get started.

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Apple’s Reality Composer: Put the Moon in Orbit with Augmented Reality

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Augmented reality is a term we’ve all heard of, but few developers are able to create immersive AR experiences — it often requires 3D design skills that are often missed in software development courses.

Thankfully, Apple’s Reality Composer makes it easy to build quick, immersive experiences without having experience with CAD and 3D modeling. While beginners can start with this tutorial, I strongly recommend checking out my previous tutorial for a more basic look at Reality Composer.

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Edge AI: The Ultimate Guide to Vision Processing Units (VPUs)

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It’s Friday. I’m checking my phone for the 30th time in the last hour. It’s 1:02 P.M. Something’s wrong. The UPS courier is late. They said it would arrive by 1 P.M — why is it not here? I was preparing one of my fresh daily emails, but I couldn’t focus. And suddenly… DING DONG! 🔔 He’s here! I suddenly felt super excited. It felt like Christmas. This morning, I received my OAK-D Camera…

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Exploring Language Models for Neural Machine Translation (Part One): From RNN to Transformers

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The main aim of this article is to introduce you to language models, starting with neural machine translation (NMT) and working towards generative language models.

For the purposes of this tutorial, even with limited prior knowledge of NLP or recurrent neural networks (RNNs), you should be able to follow along and catch up with these state-of-the-art language modeling techniques.

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Evolving Your iOS App’s Intelligence with Core ML Model Deployment

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WWDC20 has dropped a ton of great updates for developers and users. Noticeable throughout the Keynote and Platforms State of the Union addresses were mentions of Core ML models powering some incredible first-party features, such as the sleep training capabilities. ML continues to play a key role in Apple’s vision for the future.

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SwiftUI + Vision Contour Request — Coin Detection in iOS

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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.

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Social Distance Detector with Python, YOLOv4, Darknet, and OpenCV

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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.

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Demystifying Batch Normalization

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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.

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