Tweet Emotion Recognition with TensorFlow
Skills:
Supervised Learning90%
Key Takeaways
Creates a recurrent neural network to recognize emotions in tweets using TensorFlow
Original Description
In this 2-hour long guided project, we are going to create a recurrent neural network and train it on a tweet emotion dataset to learn to recognize emotions in tweets. The dataset has thousands of tweets each classified in one of 6 emotions. This is a multi class classification problem in the natural language processing domain. We will be using TensorFlow as our machine learning framework.
You will need prior programming experience in Python. This is a practical, hands on guided project for learners who already have theoretical understanding of Neural Networks, recurrent neural networks, and optimization algorithms like gradient descent but want to understand how to use the Tensorflow to start performing natural language processing tasks like text classification. You should also have some basic familiarity with TensorFlow.
Note: This course works best for learners who are based in the North America region. We’re currently working on providing the same experience in other regions.
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