Channel: Learn By Watch

Category: Education

Tags: machine learning forward propagationrecurrent neural networkrecurrent neural network explainedrecurrent neural network machine learningforward propagation neural networkrnn architecture explainedrecurrent neural network useswhat is rnnwhy rnnrnn tutorialwhat is recurrent neural networkrnnmachine learning rnnrnn neural networkrecurrent neural networks (rnns)forward propagation in rnnrecurrent neural networks are used forintroduction to rnn

Description: Recurrent neural networks (RNN) are the state of the art algorithm for sequential data and are used by Apple's Siri and and Google's voice search. It is the first algorithm that remembers its input, due to an internal memory, which makes it perfectly suited for machine learning problems that involve sequential data. In this video you will learn about these topics: ● Where all RNN is useful - Main area is natural language processing like ○ Text generation ○ Language translation ○ Sentiment analysis ○ Speech recognition ● Why RNN is helpful in these areas - Looked at why normal neural networks does not perform well on NLP problems: ○ Takes all inputs at the same time ○ Inputs may not be of same size so normal NN are not useful ○ Cannot understand the difference in positions of words ● Encoding text data to numerical data - Three steps were discussed: ○ Bag words ○ One hot encoding ○ Word embeddings - most used when dealing with NLP ● Forward propagation in RNN - Explanation of working of RNN layer with help of diagram and also the formulas behind it