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AI Engineer - Learn how to integrate AI into software applications
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Learn to build computer vision applications using Keras through this comprehensive tutorial series spanning over 3 hours. Begin by installing Keras and OpenCV, then progress through creating layers and building Sequential models. Explore Conv2D layers and understand feature maps before implementing max pooling layers. Master the use of Flatten and Dense layers, and culminate your learning by constructing a complete VGG16 image classification model from scratch. Gain hands-on experience with deep learning frameworks while developing practical skills in neural network architecture design for computer vision tasks.
Syllabus
Install Keras and OpenCV | Computer Vision with Keras
Create layers | Computer Vision with Keras p.1
Build a Sequential model | Computer Vision with Keras p.2
Conv2D Layer | Computer Vision with Keras p.3
Feature map | Computer Vision with Keras p.4
Max pooling layer | Computer Vision with Keras p.5
Flatten and Dense layers | Computer Vision with Keras p.6
Image Classification model VGG16 from scratch | Computer Vision with Keras p.7
Taught by
Pysource