- Artificial Neural Networks
- Deep Learning
- Tensorflow
- Predictive Modeling
- Data Processing
- Keras (Neural Network Library)
- Computer Vision
- Machine Learning Methods
- Applied Machine Learning
- Machine Learning
- Image Analysis
- Python Programming
Explainable AI: Scene Classification and GradCam Visualization
Completed by AYATALLAH SABRY MOHAMED ABDELRAHMAN SARHAN
August 1, 2020
1 hours (approximately)
AYATALLAH SABRY MOHAMED ABDELRAHMAN SARHAN'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
