10# InceptionResNetV2 | Image Classification | Real-Time Industrial AI Vision using ImageNet

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In this video, we demonstrate image classification using a pre-trained InceptionResNetV2 model with ImageNet, implemented in Python using TensorFlow.

The goal of this project is to introduce the fundamentals of computer vision by showing how a lightweight convolutional neural network can classify images without training a custom model.

You will learn how to :
- Load a pre-trained InceptionResNetV2 model
- Perform image classification using ImageNet classes
- Run inference on an image.
- Understand the strengths and limitations.

This video is ideal for :
- Beginners in computer vision
- Python developers
- AI & machine learning enthusiasts
- Automation and industrial engineers
- Students learning deep learning fundamentals

The demonstration is done using :
- Python
- TensorFlow / Keras
- InceptionResNetV2
- ImageNet pre-trained weights

ImageNet Dataset used in this video:
https://deeplearning.cms.waikato.ac.nz/user-guide/class-maps/IMAGENET/

This content is part of the Industrial AI Series, where we explore practical and real-world computer vision models step by step.

If you’re interested in artificial intelligence, computer vision, and industrial AI applications, don’t forget to like, subscribe, and share!

#ia #deeplearning #classification

Chapters :
00:00 Introduction
00:08 InceptionResNetV2

Видео 10# InceptionResNetV2 | Image Classification | Real-Time Industrial AI Vision using ImageNet канала IndusCore Tech