Machine Learning Use Case

Bot Detection

Bots can run havoc on social media apps, video game platforms, review sites, and more. Detecting these bots to filter unwanted content is critical. Learn how to build an end-to-end machine learning pipeline to automatically detect bots.

The Predibase Solution

Detect bots to protect your users from unwanted content

  • Rapidly preprocess tabular, text and image features
  • Finely tune model parameters such as using pre-trained encoders like Bert with little-to-no-code
  • Automate the detection of twitter bots to improve content moderation

Multimodal Data

User Demographics
User Demographics
Profile Description
Profile Description
User Posts
User Posts
Post Time Stamp
Post Time Stamp
Profile Image
Profile Image
Bot
 Detection

Business Value

Identify real vs. fake users
Identify real vs. fake users
Prevent bad actors
Prevent bad actors
Moderate unwanted content
Moderate unwanted content

Train your first bot detection model in < 20 lines of a config file

At the core of Predibas is Ludwig, an open-source declarative ML framework, that automates complex model development with a simple configuration file. Predibase builds on these capabilities with a collaborative, easy-to-use, and fully managed ML platform in the cloud.

bot-detection-screen

Resources to Get Started

Ready to accelerate your model building?