What Are They? RNNs are like learners with short-term memory – they remember recent information but get fuzzy as time passes. Simply put, a Recurrent Neural Network (RNN) is like a “learner” with memory. Imagine this learner reading an article, remembering the meaning of each word temporarily before moving on to the next. While traditional neural networks treat each input independently (like starting from scratch each time), RNNs “remember” previous information (earlier words) and pass this memory to the next step, creating context for the entire sentence....

Imagine you’re in a classroom with many students, each with their own name. The teacher wants to assign tasks based on students’ names, but the names themselves are meaningless and can’t help the teacher make decisions directly. So, the teacher assigns each student a number, like Xiaoming is No. 1 and Xiaohong is No. 2. These numbers act as “labels” for the students, helping the teacher organize them better. However, the numbers alone aren’t enough, as they don’t carry much information....