Long Short Term Memory (LSTM) | Forget, Input & Output Gate | Constant Error Carousel | Explained

RoboSathi · Beginner ·🧬 Deep Learning ·2mo ago

About this lesson

📘 Notes: https://robosathi.com/docs/natural_language_processing/lstm/ 🎥 NLP Playlist: https://www.youtube.com/playlist?list=PLnpa6KP2ZQxcDlHCeNiKbRhLWKVunQaxn 🎥 RNN: https://youtu.be/jSj1STepMA8 🎥 BPTT: https://youtu.be/-6aCFeOu4ng ✅ This video describes how the LSTM improves the RNN architecture, introducing a long term memory (cell state) along with the short term memory (hidden state). ✅ We will also understand in detail with maths: 👉 Forget, Input & Output Gates, 👉 Back Propagation Through Time 👉 Constant Error Carousel 🕔 Time Stamp 🕘 00:00:00 - 00:01:00 Introduction 00:01:01 - 00:02:07 Issue with RNN Architecture (Long Range Dependency) 00:02:08 - 00:03:17 What is LSTM ? 00:03:18 - 00:04:35 LSTM Memory Cell 00:04:36 - 00:05:27 LSTM Architecture 00:05:28 - 00:07:46 Forget Gate 00:07:47 - 00:13:56 Input Gate & Candidates 00:13:57 - 00:15:21 Output Gate 00:15:22 - 00:16:19 Usage of Sigmoid, TanH & Element Wise Dot Product Explained 00:16:20 - 00:20:31 Back Propagation Through Time 00:20:32 - 00:23:02 Constant Error Carousel 00:23:03 - 00:24:15 Summary of all Gates 00:24:16 - 00:24:55 Next: GRU

Original Description

📘 Notes: https://robosathi.com/docs/natural_language_processing/lstm/ 🎥 NLP Playlist: https://www.youtube.com/playlist?list=PLnpa6KP2ZQxcDlHCeNiKbRhLWKVunQaxn 🎥 RNN: https://youtu.be/jSj1STepMA8 🎥 BPTT: https://youtu.be/-6aCFeOu4ng ✅ This video describes how the LSTM improves the RNN architecture, introducing a long term memory (cell state) along with the short term memory (hidden state). ✅ We will also understand in detail with maths: 👉 Forget, Input & Output Gates, 👉 Back Propagation Through Time 👉 Constant Error Carousel 🕔 Time Stamp 🕘 00:00:00 - 00:01:00 Introduction 00:01:01 - 00:02:07 Issue with RNN Architecture (Long Range Dependency) 00:02:08 - 00:03:17 What is LSTM ? 00:03:18 - 00:04:35 LSTM Memory Cell 00:04:36 - 00:05:27 LSTM Architecture 00:05:28 - 00:07:46 Forget Gate 00:07:47 - 00:13:56 Input Gate & Candidates 00:13:57 - 00:15:21 Output Gate 00:15:22 - 00:16:19 Usage of Sigmoid, TanH & Element Wise Dot Product Explained 00:16:20 - 00:20:31 Back Propagation Through Time 00:20:32 - 00:23:02 Constant Error Carousel 00:23:03 - 00:24:15 Summary of all Gates 00:24:16 - 00:24:55 Next: GRU

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Chapters (13)

00:01:00 Introduction

1:01 00:02:07 Issue with RNN Architecture (Long Range Dependency)

2:08 00:03:17 What is LSTM ?

3:18 00:04:35 LSTM Memory Cell

4:36 00:05:27 LSTM Architecture

5:28 00:07:46 Forget Gate

7:47 00:13:56 Input Gate & Candidates

13:57 00:15:21 Output Gate

15:22 00:16:19 Usage of Sigmoid, TanH & Element Wise Dot Product Explained

16:20 00:20:31 Back Propagation Through Time

20:32 00:23:02 Constant Error Carousel

23:03 00:24:15 Summary of all Gates

24:16 00:24:55 Next: GRU

RNNs Explained in 60 Seconds #ai #coding #machinelearning