NLP Tutorial 14 - TF2.0 and Keras for Word Embedding in NLP on Twitter Sentiment Data | KGP Talkie

Описание к видео NLP Tutorial 14 - TF2.0 and Keras for Word Embedding in NLP on Twitter Sentiment Data | KGP Talkie

In this video, we will learn word embedding and NLP with TensorFlow 2.0 and Keras on Twitter sentiment data. Natural Language Processing(NLP) refers to computer systems designed to understand human language. Human language, like English or Hindi, consists of words and sentences, and NLP attempts to extract information from these sentences. Machine learning and deep learning algorithms only take numeric input so how do we convert text to numbers?

This is the sentiment140 dataset. It contains 1,600,000 tweets extracted using the twitter api. We are going to use 4000 tweets for training our model. The tweets have been annotated (0 = negative, 1 = positive) and they can be used to detect sentiment.

🔊 Watch till last for a detailed description
03:52 What is word embedding?
09:22 Get started with code
34:17 Compile the model
40:10 Prediction using mode

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