Tweet Emotion Recognition with TensorFlow

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In this Guided Project, you will:

Use a Tokenizer in TensorFlow

Pad and Truncate Sequences

Create and Train a Recurrent Neural Network

Use NLP and Deep Learning to perform Text Classification

Clock2 hours
IntermediateIntermediate
CloudNo download needed
VideoSplit-screen video
Comment DotsEnglish
LaptopDesktop only

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.

Skills you will develop

Natural Language ProcessingDeep LearningMachine LearningTensorflowkeras

Learn step-by-step

In a video that plays in a split-screen with your work area, your instructor will walk you through these steps:

  1. Introduction

  2. Setup and Imports

  3. Importing Data

  4. Tokenizer

  5. Padding and Truncating Sequences

  6. Preparing Labels

  7. Creating and Training RNN Model

  8. Model Evaluation

How Guided Projects work

Your workspace is a cloud desktop right in your browser, no download required

In a split-screen video, your instructor guides you step-by-step

Frequently asked questions

Frequently Asked Questions

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