MACHINE LEARNING APPLICATION IN ROBOTIC (4 SCU)

Learning Outcomes:

On successful completion of this course, students will be able to: explain  fundamental concepts of machine learning; solve  problem related to computer engineering using deep neural network; build a simulation / deep learning application using open-source software libraries and image processing tools  ; explain acquired knowledge related to deep learning, neural network design, and its application.

Topics:

1. Introduction to Deep Learning;
2. Mathematical Building Blocks of Neural Networks;
3. Introduction to Keras and TensorFlow;
4. Neural Network Classification and Regression;
5. Fundamentals of Machine Learning;
6. Universal Workflow of Machine Learning;
7. Neural Network Model with Keras;
8. Introduction to Deep Learning for Computer Vision;
9. Advanced Deep Learning for Computer Vision;
10. Deep Learning for Timeseries;
11. Deep Learning for Text;
12. Generative Deep Learning;
13. Project Presentation.