In this liveProject, you’ll take on the role of a data engineer working for an app development company. Your boss has a great idea for a new app that can automatically identify what food is shown in an image—perfect for when you want to post your lunch on social media! They have asked you to build it for them.
Your challenge is to train an image classification system using TensorFlow, and then deploy that system to production so that it can run in the web browser and as a mobile application. To do this, you’ll make use of the Python and TensorFlow ecosystems to create your model, then package it for deployment using Docker and Expo.
This project is designed for learning purposes and is not a complete, production-ready application or solution.
The liveProject is for intermediate Python programmers who know the basics of data science and some experience training an image classifier using deep learning who want to improve their experience of deploying models into production.
- Intermediate Python
- Basic Git
- Basics of TensorFlow
- Basic machine learning techniques
- Basics of neural networks
you will learn
In this liveProject, you’ll undertake the development work required to bring a deep learning model into production as both a web and mobile application. These important skills are essential for any data scientist who wants to put their expertise into action outside of the lab.
- Train deep learning models using the Colab GPU, TensorFlow, and Keras
- Deploy deep learning models using TensorFlow.js
- Create web applications with Expo and React Native, and Heroku and GitHub pages
- Deploy your web application using Docker
- Deploy a mobile application using Expo, Node.js, and NVM