Data Science and Machine Learning (Theory and Projects) A to Z - Data Preparation and Preprocessing: Handling Video and

The video tutorial explains how to represent images, videos, and audio as feature vectors for machine learning. It covers the conversion of images and videos into numeric forms, emphasizing the importance of feature vectors in classification tasks. The tutorial also discusses the use of CNNs and RNNs for handling large datasets and varying data lengths. Audio data is addressed, highlighting its inherent numeric form and the challenges of varying lengths. The video concludes with a brief mention of text data, setting the stage for the next tutorial.

What challenges arise when working with audio signals of different lengths?

Describe the importance of having a consistent number of features across different samples.

What techniques can be used to convert text data into numeric form for machine learning?