Deploy an NLP Text Generator: Bart Simpson Chalkboard Gag

Offered By
In this Guided Project, you will:

Deploy a trained NLP text generator model as a web app

1.5 hours
No download needed
Split-screen video
Desktop only

Welcome to the “Deploy an NLP Text Generator: Bart Simpson Chalkboard Gag” guided project. Text Generation is a natural language technique that leverages language modeling to create or predict new text based on texts it has been trained on. An example of text generation can be identified in the Gmail sentence autocomplete feature. In this project, we will deploy an NLP text generator model as a python Streamlit app. The model, which has been trained on all the text from Bart Simpsons chalkboard gag from the Simpsons, will be able to autogenerate new chalkboard gags. This project is an intermediate python project for anyone interested in learning about how to productionize natural language text generator models as a Streamlit app on Heroku. It requires preliminary knowledge on how to build and train NLP text generator models (as we will not be building or training models) and how to utilize Git. Learners would also need a Heroku account and some familiarity with the Python Streamlit module. At the end of this project, learners will have a publicly available Streamlit web app that leverages natural language processing text generation to generate new text for Bart Simpsons' chalkboard gags.

Skills you will develop

  • Natural Language Processing

  • Python Programming

  • Streamlit

  • Natural Language Generation

  • ML Deployment

Learn step-by-step

In a video that plays in a split-screen with your work area, your instructor will walk you through these steps:

  1. Importing all the necessary libraries, model and data

  2. Creating the text generator function

  3. Creating streamlit app UI

  4. Deploying app to Heroku

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Your workspace is a cloud desktop right in your browser, no download required

In a split-screen video, your instructor guides you step-by-step

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You'll learn by doing through completing tasks in a split-screen environment directly in your browser. On the left side of the screen, you'll complete the task in your workspace. On the right side of the screen, you'll watch an instructor walk you through the project, step-by-step.