Creating Anime characters using GAN & Implementing in Gradio
Explore the fascinating world of Anime Character Creation in a Gradio web app. Fine-tune multiple functions to generate diverse characters and analyze their intercorrelations, enabling you to create unique anime characters from scratch.

Language
- English
Topic
- Artificial Intelligence
Enrollment Count
- 114
Skills You Will Learn
- Artificial Intelligence, Machine Learning, PyTorch, Python
Offered By
- IBM
Estimated Effort
- 45 minutes
Platform
- SkillsNetwork
Last Update
- May 10, 2025
A Look at the Project Ahead
- Image Generation with GANs: You will explore the process of generating images using GANs, including the generation of unique and diverse animated character images through interaction with the trained GAN model.
- Gradio: You will utilize Gradio, a Python library, to create a user-friendly interface for interacting with the trained GAN model and generating unique and diverse animated character images. Gradio simplifies the process of integrating the GAN model into a web application by providing pre-built components for input and output interfaces. This allows users to easily customize and generate animated character images by interacting with the GAN model through the web application.
What You'll Need

Language
- English
Topic
- Artificial Intelligence
Enrollment Count
- 114
Skills You Will Learn
- Artificial Intelligence, Machine Learning, PyTorch, Python
Offered By
- IBM
Estimated Effort
- 45 minutes
Platform
- SkillsNetwork
Last Update
- May 10, 2025
Instructors
Joseph Santarcangelo
Senior Data Scientist at IBM
Joseph has a Ph.D. in Electrical Engineering, his research focused on using machine learning, signal processing, and computer vision to determine how videos impact human cognition. Joseph has been working for IBM since he completed his PhD.
Read moreRoodra Kanwar
Data Scientist at IBM
I am a data scientist by day, superhero by night. Psych! I wish I was that cool. Only the former part is true which is still pretty cool! I believe in constant learning and it is an essential part of being a productive data enthusiast. I am also pursuing my masters in computer science from Simon Fraser University specializing in Big Data. Moreover, knowledge is transfer learning (pun intended!) and what I have gained, I plan on reflecting it back to the data community.
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