Tweet Emotion Recognition with TensorFlow

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Coursera Project Network
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在此免費指導項目中,您將:

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

在面試中展現此實踐經驗

Clock2 hours
Intermediate中級
Cloud無需下載
Video分屏視頻
Comment Dots英語(English)
Laptop僅限桌面

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.

必備條件

Prior programming experience in Python, familiarity with TensorFlow, theoretical understanding of recurrent neural networks.

您要培養的技能

  • Natural Language Processing
  • Deep Learning
  • Machine Learning
  • Tensorflow
  • keras

分步進行學習

在與您的工作區一起在分屏中播放的視頻中,您的授課教師將指導您完成每個步驟:

  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

指導項目工作原理

您的工作空間就是瀏覽器中的雲桌面,無需下載

在分屏視頻中,您的授課教師會為您提供分步指導

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