🤖 AI Without Transformers How 🔁 RNN, 🛠️ LSTM & 🕰️ GRU Dominated NLP [Part 3/6]

Welcome to AI without Transformers! 🚀🧠
Before the rise of Transformers, RNNs, LSTMs, and GRUs ruled the world of Natural Language Processing (NLP)! 🌍📚

00:00 Visual examples
00:56 Training RNN
03:10 Weight and Backpropagation
04:41 Short-Term Memory limitations
05:13 Vanishing gradient
05:53 Long Short-Term Memory
06:36 Gated Recurrent Unit

Before the rise of Transformers, RNNs, LSTMs, and GRUs ruled the world of Natural Language Processing (NLP)! 🌍📚

In this video, we take a journey through time ⏳ to discover how these models worked, why they were revolutionary 💥, and what challenges they faced ⚡ (like the vanishing gradient problem!).

✨ What you'll explore:
🔄 How RNNs process sequences of data
🧩 How LSTM and GRU improved memory handling
⚡ Why traditional models struggled with long sequences
🏛️ How these architectures shaped the history of NLP

Whether you're a beginner 👶 or an AI enthusiast 🧠, this is your chance to connect with the foundations of modern AI!

Hit LIKE ❤️, leave a COMMENT ✍️, and SUBSCRIBE 🔔 for more amazing AI journeys!

#AI #NLP #DeepLearning #MachineLearning #historyofai