Let’s build an insultbot

Getting ready to welcome trollers and alike
(2) Ratings
3,787 students
Created by Jorge Guerra Pires

What you'll learn

  • How to use a pretrained model for content moderation
  • Using Angular Material, basics
  • Implementing artificila intelligence in Angular
  • How to use TensorFlowjs (deep learning)
This course includes:
3 total hours on-demand video
0 articles
0 downloadable resources
22 lessons
Full lifetime access
Access on mobile and TV
Certificate of completion

Course content


  • No programming experience needed, basics of Angular may be beneficial


“even the prime minister of Norway herself, reposted the photo to Facebook, only to have it quickly removed.” Custodians of the Internet (Tarleton Gillespie)

A very nice application of artificial intelligence is on content moderation. Our goal is spotting whether a content has something that should not be shown on a conversation. On this course, we use TensorFlow.js (machine learning in JavaScript), a pretrained model, for content moderation. It is very easy to use: just call the model and get a reply, a list of types of contents to be blocked and their respective flags.

Online Content moderation is the process by which one must decide what stays online vs. what should be moderated or even eliminated; no one is happy to be moderated, I was not when I was the target of several online moderations on YouTube, Facebook and Twitter. The “Napalm girl” was a famous case in which Facebook classified as nudity, which is a historical picture.

What is the best and most efficient way to safely moderate content online?

Several programming savvies are doing their best. Like in String Theory, they gather the best, but no practical answer came out yet. Recently, we had chatGPT that can make sentiment analysis in an advance approach, this course shows an alternative, which is free. chatGPT has a small chart per API call. Furthermore, chatGPT requires much less coding expertise

On this course, I want to share a trivial case, which was not also easy to solve for a scientists, but now easily implemented as public library: direct insult (i.e., calling people names).

The bot is a classical pattern recognition: it gives out a number, and you must decide your tolerance for insults. This number, already standard on deep learning, is a sort of probability, loosely speaking.

We are going to use two MIT license Google public tools: TensorFlow.js and Angular. The former is a deep learning tool for freely creating smart web application, whereas the latter is a free framework for creating frontend application, no need to create servers.

Who this course is for:

  • Angular programmers interested in artificial intelligence
  • Artificial intelligence practitioners interested in web development
  • People interested in online content moderation
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