Data Science and Machine Learning (Theory and Projects) A to Z - Feature Engineering: Derived Features Histogram of Grad

The video tutorial discusses traditional and modern methods of feature extraction in image processing. It covers Histogram of Oriented Gradients (HOG) and Local Binary Patterns (LBP) as traditional methods, explaining their processes and applications. The tutorial also highlights the impact of deep neural networks (DNNs) in automating feature extraction, reducing the need for manual feature design. The video concludes with a brief mention of upcoming topics on data preprocessing.

What are some traditional methods for converting raw images into feature vectors?

Discuss the role of feature vectors in machine learning and data science.

How have deep neural networks (DNNs) changed the approach to feature vector design?