Prototyping With Gradio
Published 6/2022
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz
Language: English | Size: 1.28 GB | Duration: 3h 13m

Build and Deploy your DEMOs from Scratch with the incredible GRADIO! Seat with me and start CODING TOGETHER!
What you'll learn
Building complete DEMOs of your Machine Learning Models from Scratch using Gradio
Getting strong Skills about ALL Gradio's Basic and Advanced Features
Deploying your DEMOs on Huggingface Spaces
Managing TextBox, Images, Checkbox, Multiple Inputs/Outpus, Authentication, Logging, Flagging and APIs in Gradio
Requirements
Python (or any programming language) basic knowledge
Description
Let's build-up and deploy DEMOs of your Machine Learning Models together from SCRATCH!Sometimes the best way to learn is not study tons of pages but start doing things together with experts. In this course you are invited to seat together with me coding and making DEMOs step-by-step, instruction after instruction.Building-up and Deploying simple and more advanced DEMOS of your Machine Leaning Models from Scratch using GRADIO is the best way to acquire all the SKILLS needed to create any kind of web Interface as complex and as big as you want. With this approach you will move from zero to hero in a real blink of an eye!In these videos we see how to build up a simple Interface and a simple related DEMO leveraging the incredible framework named GRADIO.In the Advanced Part we learn how to give Login and Authentication features to our DEMOs and how to manage the API to use our Machine Leaning Models with a simple POST call.Once our Interfaces and DEMOs are completed and tested we publish them online using Huggingface Spaces.No installations required at all on your machine, we are doing everything online with Google Colab and Huggingface Spaces (for sure if you want you can use you local Jupyter Notebook installation).Don't hesitate to contact me for any kind of question!CHEERS!
Overview
Section 1: Dealing with Interfaces
Lecture 1 Introduction to Gradio
Lecture 2 Gradio 1st Interface
Lecture 3 Text, Image and Data Frame
Lecture 4 Multiple Inputs and Multiple Outputs
Lecture 5 Debugging and Flagging
Lecture 6 UI and UX Improvement
Section 2: Advanced Features
Lecture 7 Login and Authenticatrion
Lecture 8 Deployment on Huggingface Spaces
AI Professionals, Python Programmers, Machine Learning Students, Computer Science Students, IT Passionates
Screenshots