Deploying a Deep Learning Model on Web and Mobile Applications

prerequisites
Intermediate Python, Basic Git, Basics of TensorFlow, Basic machine learning techniques, Basics of neural networks
skills learned
Train a Deep Learning model, Deploy a Deep Learning model using TensorFlow.js, Create web applications, Deploy your application using Docker
Nidhin Pattaniyil and Reshama Shaikh
3 weeks · 7-10 hours per week · INTERMEDIATE
Look inside
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.

book resources

When you start your liveProject, you get full access to the following books for 90 days.

project authors

Nidhin Pattaniyil
Nidhin Pattaniyil is a Machine Learning Engineer at Walmart. He has extensive experience working on the full lifecycle of a machine learning project, creating NLP models and building experiences around it. He has been a mentor in Udacity’s NLP course, and has an M.S. in Computer Science.
Reshama Shaikh
Reshama Shaikh is an independent data scientist and statistician. She has an M.S. in Statistics and an M.B.A. from NYU Stern with a focus on business analytics and technology. She has over 10 years experience working on clinical trials at pharmaceutical companies, and has been doing research and work in data science and deep learning for the past 5 years.

Prerequisites

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.

TOOLS
  • Intermediate Python
  • Basic Git
  • Basics of TensorFlow
TECHNIQUES
  • 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

features

Self-paced
You choose the schedule and decide how much time to invest as you build your project.
Project roadmap
Each project is divided into several achievable steps.
Get Help
While within the liveProject platform, get help from other participants and our expert mentors.
Compare with others
For each step, compare your deliverable to the solutions by the author and other participants.
book resources
Get full access to select books for 90 days. Permanent access to excerpts from Manning products are also included, as well as references to other resources.
Look inside

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