What is LSTM ?| Long Short Term Memory Explained with Example | Deep Learning Tutorial | Simplilear

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In this video on What is LSTM, we will go through what is LSTM, moving forward we will learn what is RNN, and after this, we will see the types of gates in LSTM and some applications of LSTM. At the end of the video, we will see a hands-on lab demo of gold price prediction using the LSTM model in machine learning.

00:00 What is LSTM?
01:51 What is RNN?
02:29 Types of gates in LSTM
03:45 Applications of LSTM
05:40 Hands-on lab demo

Dataset link: https://drive.google.com/drive/folders/1_tH5KivzpFL83-3mIY4Da-ELHBM0Vv7b?usp=share_link

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What is RNN?

RNNs are a type of neural network that are designed to process sequential data. They can analyze data with a temporal dimension, such as time series, speech, and text. RNNs can do this by using a hidden state passed from one timestep to the next. The hidden state is updated at each timestep based on the input and the previous hidden state. RNNs are able to capture short-term dependencies in sequential data, but they struggle with capturing long-term dependencies.

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