filmov
tv
Attention Mechanism in 1 video | Seq2Seq Networks | Encoder Decoder Architecture
Показать описание
In this video, we introduce the importance of attention mechanisms, provide a quick overview of the encoder-decoder structure, and explain how the workflow functions.
An attention mechanism is a key concept in the field of machine learning, particularly in the context of sequence-to-sequence (Seq2Seq) models with encoder-decoder architecture. Instead of processing an entire input sequence all at once, attention mechanisms allow the model to focus on specific parts of the input sequence while generating the output sequence. This mimics the human ability to selectively attend to different elements when processing information. Watch the video till the end to develop a deep understanding about this concept.
============================
Do you want to learn from me?
============================
📱 Grow with us:
👍If you find this video helpful, consider giving it a thumbs up and subscribing for more educational videos on data science!
💭Share your thoughts, experiences, or questions in the comments below. I love hearing from you!
⌚Time Stamps ⌚
00:00 - 00:55 - Intro
00:56 - 08:39 - The Why
08:40 - 11:20 - The Solution
11:21 - 41:10 - The What
41:11 - 41:23 - Conclusion
✨ Hashtags✨
#DataScience #MachineLearning #Deeplearning #CampusX
An attention mechanism is a key concept in the field of machine learning, particularly in the context of sequence-to-sequence (Seq2Seq) models with encoder-decoder architecture. Instead of processing an entire input sequence all at once, attention mechanisms allow the model to focus on specific parts of the input sequence while generating the output sequence. This mimics the human ability to selectively attend to different elements when processing information. Watch the video till the end to develop a deep understanding about this concept.
============================
Do you want to learn from me?
============================
📱 Grow with us:
👍If you find this video helpful, consider giving it a thumbs up and subscribing for more educational videos on data science!
💭Share your thoughts, experiences, or questions in the comments below. I love hearing from you!
⌚Time Stamps ⌚
00:00 - 00:55 - Intro
00:56 - 08:39 - The Why
08:40 - 11:20 - The Solution
11:21 - 41:10 - The What
41:11 - 41:23 - Conclusion
✨ Hashtags✨
#DataScience #MachineLearning #Deeplearning #CampusX
0:05:34
Attention mechanism: Overview
0:26:10
Attention in transformers, visually explained | Chapter 6, Deep Learning
0:04:30
Attention Mechanism In a nutshell
0:41:24
Attention Mechanism in 1 video | Seq2Seq Networks | Encoder Decoder Architecture
0:15:01
Illustrated Guide to Transformers Neural Network: A step by step explanation
0:04:44
Self-attention in deep learning (transformers) - Part 1
0:21:02
The Attention Mechanism in Large Language Models
0:14:32
Rasa Algorithm Whiteboard - Transformers & Attention 1: Self Attention
1:03:37
Understanding Positional Encodings (the KEY to Transformers)
0:27:14
How large language models work, a visual intro to transformers | Chapter 5, Deep Learning
0:15:51
Attention for Neural Networks, Clearly Explained!!!
0:27:07
Attention Is All You Need
0:58:04
Attention is all you need (Transformer) - Model explanation (including math), Inference and Training
0:07:49
Attention Mechanism in Computer Vision (EE432 Course Presentation)
0:20:21
Attention Mechanism - Introduction to Deep Learning
0:21:31
Efficient Self-Attention for Transformers
0:36:15
Transformer Neural Networks, ChatGPT's foundation, Clearly Explained!!!
0:15:25
Visual Guide to Transformer Neural Networks - (Episode 2) Multi-Head & Self-Attention
0:05:49
Attention Mechanism | Deep Learning
0:15:02
Self Attention in Transformer Neural Networks (with Code!)
0:22:30
Lecture 12.1 Self-attention
0:11:19
Attention in Neural Networks
0:09:42
C5W3L07 Attention Model Intuition
0:07:05
Convolutional Block Attention Module (CBAM) Paper Explained
Комментарии