- Published on November 2, 2020
- In Deep Tech
Deploying Machine Learning Models In Android Apps Using Python
- By Kaustubh Gupta
After working on the model building, the next step in the machine learning life cycle is usually the deployment in the real-world scenario to perform actionable tasks. In most cases, the model is deployed via the web interfaces, android apps, or IoT. Where the website deployment requires a lot of extra effort to set up the front-end, android apps seems a reasonable solution, and that too when the app is built in Python! In this article, I will walk you through building apps using Python, which will be a cross-platform application, meaning it can be converted into android apps and IOS too.
Overview of the Article
Introduction to the problem statementDeveloping the APIKivy and Kivymd BasicsFinishing the AppConclusion
Problem Statement
The dataset for which we will build the model
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Kaustubh Gupta
I am a Python Developer capable of Web Scraping, Selenium Automation, Data Science, Backend Web Development with knowledge of CSS and Bootstrap, developing android apps in Python, contribution in open source organization (IOSF). Content Writing is my current hobby, written around 100+ articles as a freelancer, personal blogs for my website, and medium blogs. Do check out my projects and star them if you find them useful :-)
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