Deep Learning Course | Natural Language Processing with TensorFlow | RNNs and LSTMs with TensorFlow

3. Classification with RNNs and LSTMs
Introduction to RNNs
Implementing LSTMs with TensorFlow
Improving your movie review classifier
Challenge: Yelp review classifier
Solution: Yelp review classifier

There is a growing demand to harness the power of natural language processing (NLP) and deep learning models to be able to make sense of textual data and reduce the emotional intervention of humans in order to make better decisions. In this course, instructor Harshit Tyagi provides a complete guide to understanding NLP using recurrent neural networks (RNNs). Harshit begins by introducing you to word encodings and using TensorFlow for tokenization. He describes the important concept of word embeddings and shows you how to use TensorFlow to classify movie reviews and project vectors. Harshit discusses RNNs and long short-term memory (LSTM), then shows you how to improve the movie review classifier from earlier in the course. He concludes with a discussion of how you can train RNNs to predict the next word in a sentence, which in turn allows you to generate some original text.
#deeplearning #nlp #NLP #naturallearning #tensorflow #rnn
TensorFlow Tutorial 6 - RNNs, GRUs, LSTMs and Bidirectionality
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What is LSTM (Long Short Term Memory)?
#AI #LSTM #RNN
LSTM
Long Short Term Memory
RNN
Recurrent Neural Networks
AI
Artificial Intelligence
IBM
Long Short-Term Memory for NLP
Simple Explanation of LSTM | Deep Learning Tutorial 36 (Tensorflow, Keras & Python)
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