Understanding Naive Bayes & its applications in text classification (Part I)

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One of the most crucial aspects of machine learning is understanding the mathematics & statistics behind it. In my journey to becoming a data scientist, I wanted to master not only the theoretical aspects of math & stats but also understand how I could apply them to my area of work.

There is an ever-increasing number of machine learning algorithms, and this post is going to focus on one of my favorites — the Naive Bayes algorithm. Specifically, I’m going to break this exploration into two parts—the first part is going to broadly cover the Naive Bayes algorithm and how it can be applied in text classification. And the second part of it is going to focus on building a REST API from the model we create in Part I. So stay tuned and enjoy!

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Train Neural Networks Using a Genetic Algorithm in Python with PyGAD

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The genetic algorithm (GA) is a biologically-inspired optimization algorithm. It has in recent years gained importance, as it’s simple while also solving complex problems like travel route optimization, training machine learning algorithms, working with single and multi-objective problems, game playing, and more.

Deep neural networks are inspired by the idea of how the biological brain works. It’s a universal function approximator, which is capable of simulating any function, and is now used to solve the most complex problems in machine learning. What’s more, they’re able to work with all types of data (images, audio, video, and text).

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Snapchat, FaceApp, and the necessary lessons of data privacy with mobile machine learning

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If you’re even remotely plugged into the tech world, you’d have been hard-pressed to miss a couple viral summer trends, both involving AI-powered photo transformations.

Here’s the gist. Snapchat caught fire and soared past all Q2 estimates, in large part because of their rollout out of popular gender-swap and baby-face Lenses. And soon after, FaceApp took the internet by storm when its old-age filter went viral. This has led to millions of users, including prominent celebrities, showing off what they’d look like in 40 years or as members of a different gender.

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Using Coil to Download Images on Android in Kotlin

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Coil is a new image loading library in Kotlin for downloading images in Android, and it’s list of strengths are impressive:

Before Coil, we often used libraries like Glide and Picasso to download images in Android. But with the improvements that we’ll cover in this article, it’s clear that Coil is the go-to choice for Android devs working with Kotlin.

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Getting Started with React Native and Expo using Hooks 2024

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We live in the world with a vast array of mobile devices, primarily dominated by two platforms: iOS and Android. It’s a two-horse race, and I’m sure we can all agree on that. Building a mobile application for both platforms is not an easy task, though.

For iOS, you write code using Objective-C or Swift, and for Android, you will find yourself using Java or Kotlin. Apart from different programming languages used to create an app that can run on each of the two platforms, the toolchains are entirely different.

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Building an Android Login System

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This tutorial builds a login system for an Android app. The app allows the users to register using a username and a password. A local server implemented in Python using Flask accepts the user data and inserts them into a MySQL database.

For securing the password, it’s encrypted using the MD5 hashing algorithm. After successful registration, the user will be able to log into the system by entering a server-verified username and password.

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