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Image Classification with Transfer Learning using TensorFlow
Image Classification with Transfer Learning using TensorFlow 2.x
Course Overview (0:41)
Welcome and Learning Objectives (1:45)
1. Modern Image Recognition (5:42)
2. Data Preprocessing (5:01)
2.1 - Go to Colab (8:50)
3. Creating Base Models from Pre-trained Convolutional Neural Networks (3:19)
4. Freezing the Convolutional Base Model (2:44)
5. Feature Extraction (2:15)
5.1-Go to Colab (7:16)
6. Adding a New Classification Layers (3:55)
7. Stack Layers, Compile and Train the Model (4:07)
8. Training Statistics and Predictions (3:04)
8.1 Go to Colab (11:28)
9. Transfer Learning-Summary and Takeaways (2:18)
Deploying Models to Mobile Devices with Pallet
10. Creating TensorFlow Lite Models (4:29)
10.1 Go to Colab (7:50)
11. Deploying Models to Android - Exploring Pallet (10:21)
12. Deploying Models from the Pallet Web Console (9:11)
13. Deploying Models from the Pallet App (7:36)
Course Updates (NEW!)
Using MobileNetV3 (3:16)
Go to Colab on Using MobileNetV3
Sample Lessons (Optional)
Build, Train, Deploy (Sample Lesson)
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9. Transfer Learning-Summary and Takeaways
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