Let build an insultbot

Lets build an insultbot, available at $19.99, has an average rating of 4.8, with 22 lectures, based on 5 reviews, and has 4010 subscribers.

You will learn about 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 is ideal for individuals who are Angular programmers interested in artificial intelligence or Artificial intelligence practitioners interested in web development or People interested in online content moderation It is particularly useful for Angular programmers interested in artificial intelligence or Artificial intelligence practitioners interested in web development or People interested in online content moderation.

Enroll now: Lets build an insultbot

Summary

Title: Lets build an insultbot

Price: $19.99

Average Rating: 4.8

Number of Lectures: 22

Number of Published Lectures: 21

Number of Curriculum Items: 22

Number of Published Curriculum Objects: 21

Original Price: R$79.90

Quality Status: approved

Status: Live

What You Will 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)

Who Should Attend

Angular programmers interested in artificial intelligence

Artificial intelligence practitioners interested in web development

People interested in online content moderation

Target Audiences

Angular programmers interested in artificial intelligence

Artificial intelligence practitioners interested in web development

People interested in online content moderation

“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.

Course Curriculum

Chapter 1: Preliminaries

Lecture 1: Meet our Gitbook, an ebook for assisting on learning

Lecture 2: Meet our app, a bot for detecting insults

Lecture 3: Meet our github repository

Chapter 2: Getting started

Lecture 1: Initials

Lecture 2: Installing @tensorflow-models/toxicity: getting ready to be insulted by trollers

Lecture 3: Getting to know the library: a basic parametrization

Lecture 4: Getting to know the library: ******, testing this insult

Chapter 3: Creating an User Interface using Angular Material

Lecture 1: Getting started

Lecture 2: Getting started, part II

Lecture 3: Using Angular Material to create a card

Lecture 4: Adding a button to our card

Lecture 5: Adding an input for moderation to our card

Lecture 6: Connect button to our logic

Lecture 7: Preparing the code for showing the moderation result from input

Lecture 8: Just some final adjustments, and we are ready to go: you suck!

Lecture 9: Closing lines, just a final test

Chapter 4: Take a pick on our course before buying it!

Lecture 1: Error type I and II on online content moderation: parametrizing @tensorflow-mode

Lecture 2: **** is a way to insult black people in America; is our bot able to flag it?

Lecture 3: Getting to know me briefly

Chapter 5: Anexo A: webinars

Lecture 1: Artificial Intelligence: An exponential growth in the last decade, past, present

Lecture 2: Computational Thinking: How computers think, decide and learn

Instructors

Jorge Guerra Pires
Independent Researcher, PhD

IdeaCoding Lab
IdeaCodingLab: Transforme sua ideia em linhas de códigos

TensorFlow.js Academy
Machine learning in JavaScript

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5 stars: 4 votes

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