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LSTM Recurrent Neural Network (RNN) | Explained in Detail 3 года назад


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LSTM Recurrent Neural Network (RNN) | Explained in Detail

LSTM Recurrent Neural Network is a special version of the RNN model. It stands for Long Short-Term Memory. The simple RNN has a problem that it cannot remember the context in a long sentence because it quickly loses information. And that is why Simple RNN has an only short-term memory. LSTM has both long-term and short-term memory. It can store any contextual information for a long time. LSTM has 2 internal states. 1.) Memory Cell State which acts as a long term memory 2.) Hidden State which acts as a short term memory The main working components in LSTM are gates. There are 3 types of gates in LSTM: 1.) Forget Gate 2.) Input Gate 3.) Output Gate In the video, we have understood LSTM Recurrent Neural Network in detail. ➖➖➖➖➖➖➖➖➖➖➖➖➖➖➖ Timestamps: 0:00 Intro 1:36 Problem with RNN 5:30 LSTM Overview 7:42 Forget Gate 10:39 Input Gate 13:39 Equations and other details 16:41 Summary of LSTM 18:23 LSTM through different times 19:01 End ➖➖➖➖➖➖➖➖➖➖➖➖➖➖➖ 📕📄 Quiz: https://forms.gle/no29DhL1pF1dsFw28 ➖➖➖➖➖➖➖➖➖➖➖➖➖➖➖ Follow my entire playlist on Recurrent Neural Network (RNN) : 📕 RNN Playlist:    • What is Recurrent Neural Network in D...   ➖➖➖➖➖➖➖➖➖➖➖➖➖➖➖ ✔ CNN Playlist:    • What is CNN in deep learning? Convolu...   ✔ Complete Neural Network:    • How Neural Networks work in Machine L...   ✔ Complete Logistic Regression Playlist:    • Logistic Regression Machine Learning ...   ✔ Complete Linear Regression Playlist:    • What is Linear Regression in Machine ...   ➖➖➖➖➖➖➖➖➖➖➖➖➖➖➖ If you want to ride on the Lane of Machine Learning, then Subscribe ▶ to my channel here:    / @machinelearningwithjay  

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