GitHub Repo
https://github.com/majorkh/CCN-model-trained
The hands on project on Scene Classification and GradCam Visualization is divided into following tasks: Task #1: Project Overview/Understand the problem statement and business case Task #2: Import Libraries/datasets and perform preliminary data processing Task #3: Perform Image Visualization Task #4: Perform Image Augmentation Task #5: Understand the theory and intuition behind Convolutional Neural Networks (CNNs) and Residual blocks. Task #6: Build ResNet-18 Model Task #7: Compile and train deep learning model Task #8: Assess the Performance of the Trained Model Task #9: Visualizing Activation Maps through Grad-CAM Task #10: Save the model for deployment Task #11: Serve the model using Tensorflow Serving I did this project from Coursera Project Network. the link of the project is given below. https://www.coursera.org/learn/scene-classification-gradcam/home/welcome The project is designed by Ryan Ahmed. Ryan is a professor who is passionate about education and technology. Ryan holds a Ph.D. degree in Mechanical Engineering from McMaster University in Canada, with focus on Mechatronics and Electric Vehicle (EV) control. He also received a Master’s of Applied Science degree from McMaster, with a focus on Artificial Intelligence (AI) and fault detection and an MBA in Finance from the DeGroote School of Business.
