- Python Programming
- Transfer Learning
- Applied Machine Learning
- Convolutional Neural Networks
- Keras (Neural Network Library)
- Tensorflow
- Machine Learning
- Model Evaluation
- Data Preprocessing
- Deep Learning
- Computer Vision
- Image Analysis
Explainable AI: Scene Classification and GradCam Visualization
Completed by YI FANG LEE
January 10, 2021
1 hours (approximately)
YI FANG LEE's account is verified. Coursera certifies their successful completion of Explainable AI: Scene Classification and GradCam Visualization
What you will learn
Understand the theory and intuition behind Deep Neural Networks, Residual Nets, and Convolutional Neural Networks (CNNs)
Build a deep learning model based on Convolutional Neural Network and Residual blocks using Keras with Tensorflow 2.0 as a backend
Visualize the Activation Maps used by CNN to make predictions using Grad-CAM and Deploy the trained model using Tensorflow Serving
Skills you will gain
