Data Science and Machine Learning (Theory and Projects) A to Z - Introduction: Focus of the Course

This course provides a comprehensive introduction to convolutional neural networks (CNNs), starting from classical computer vision techniques and progressing to advanced deep learning models. It emphasizes a Pythonic approach, using Python code to simplify complex concepts. The course covers both fundamental and high-level applications, including recent models like Mobilenet and frameworks such as Tensorflow. Students will engage in practical projects, including transfer learning and state-of-the-art object detection with YOLO, to solidify their understanding.

How does the course ensure that beginners can understand both basic and advanced concepts?

What are some of the recent models and algorithms introduced in the course?

Describe the approach taken in the course to teach the implementation of convolutional neural networks.