Image Processing Techniques
Instructor: Hüseyin Yağız Devre -UAA'22
Princeton University, New Jersey, USA
Instructor: Hüseyin Yağız Devre -UAA'22
Princeton University, New Jersey, USA
Course Description: This course will focus on the basics of machine learning and computer vision techniques. In this course, we will investigate the basics of data science and deep learning algorithms. We will start with a recap of Python Programming Language, which will be the main programming language of the course. Next, we will investigate the libraries used for training new state-of-the-art AI models. You will also be able to design and implement 2 advanced deep learning algorithms with real-life applications.
Class Size: 15 Max
Prerequisite: Preferably 11th and 12th graders with a background or interest in CS and Python
Length: 6 Weeks
Goals:
Understand the basics of machine learning with simple algorithms such as SVM, Linear-Logistic Regression
Understand the theory behind neural networks
Outline how is data processed, stored, and used in machine learning algorithms
Implement a functional deep neural network algorithm with a custom dataset.
Course Outline:
Week 1: Recap of Python Programming Language
Week 2: Introduction to Scikit-learn with SVM algorithm to classify Celestial Pulsars
Week 3: Introduction to Tensorflow with the implementation of a neural network
Week 4: Introduction to image processing and data augmentation.
Week 5: Implementation of computer vision algorithm for cancer diagnosis
Week 6: Implementation of computer vision algorithm for face recognition