YoVDO

5 Steps to Build an AI Vision MVP

Offered By: Pysource via YouTube

Tags

Computer Vision Courses Software Development Courses Deep Learning Courses OpenCV Courses Data Collection Courses

Course Description

Overview

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Learn the essential steps for creating a successful Computer Vision Minimum Viable Product (MVP) in this 17-minute video. Discover the difference between an MVP and a Proof of Concept, and explore key aspects such as problem definition, tool selection, data collection, user-friendly design, and feedback gathering. Gain valuable insights into the development process of AI vision projects and apply these principles to your own computer vision endeavors.

Syllabus

Intro
Difference between MVP and PC
Define the problem
Choose the right tools
Data collection
Simple to use
Collect feedback


Taught by

Pysource

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