Tweet Emotion Recognition with TensorFlow

35개의 평가
Coursera Project Network
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학습자는 이 무료 안내 프로젝트에서 다음을 수행하게 됩니다.

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

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Clock2 hours
Cloud다운로드 필요 없음
Video분할 화면 동영상
Comment Dots영어
Laptop데스크톱 전용

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.

요구 사항

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

개발할 기술

Natural Language ProcessingDeep LearningMachine LearningTensorflowkeras

단계별 학습

작업 영역이 있는 분할 화면으로 재생되는 동영상에서 강사는 다음을 단계별로 안내합니다.

  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

안내형 프로젝트 진행 방식

작업 영역은 브라우저에 바로 로드되는 클라우드 데스크톱으로, 다운로드할 필요가 없습니다.

분할 화면 동영상에서 강사가 프로젝트를 단계별로 안내해 줍니다.



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