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?

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

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

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