Encoding is typically used where the number of dimensions in a vector is huge. Encoding helps turn a large vector into a vector that has far fewer dimensions without losing much information from the original vector. In the following sections, let's explore the need for encoding images, text, and recommender systems.
Need for encoding
Need for encoding in text analysis
To understand the need for encoding in text analysis, let's consider the following scenario. Let's go through the following two sentences:
In traditional text analysis, the preceding two sentences are one-hot encoded, as follows:
Note that there are five unique words in the two sentences.
The preceding one-hot encoded versions of the words result...