study
youtube
🔥 Purdue Post Graduate Program In AI And Machine Learning:
🔥IIT Kanpur Professional Certificate Course In AI And Machine Learning :
🔥AI & Machine Learning Bootcamp:
🔥AI Engineer Masters Program (Discount Code - YTBE15):
🔥 Professional Certificate Program In Generative AI And Machine Learning -
In this video, we're going to explore Transformers, a groundbreaking architecture that has transformed the field of Natural Language Processing (NLP). We'll break down how Transformers work, focusing on their key components such as self-attention, multi-head attention, and the roles of the encoder and decoder. Unlike traditional models, Transformers can handle long sequences and complex dependencies more efficiently, making them the backbone of advanced models like BERT, GPT, and others.
-- Frequently Asked Questions
✅ Question 1 What is the key difference between Transformers and traditional RNN models?
Answer:Unlike RNNs, which process data sequentially and can struggle with long-range dependencies, Transformers use self-attention to process the entire input sequence at once.
✅ Question 2 What is self-attention in a Transformer, and why is it important?
Answer:Self-attention is the mechanism that allows a Transformer to focus on different parts of the input sequence when generating an output. It calculates the relationships between words in a sequence, helping the model understand context and meaning mor
|
2024/09/13
youtube
