Tweet Emotion Recognition with TensorFlow

4.9
estrellas
14 calificaciones
ofrecido por
Coursera Project Network
En este proyecto guiado, tú:

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
IntermediateIntermedio
CloudNo se necesita descarga
VideoVideo de pantalla dividida
Comment DotsInglés (English)
LaptopSolo escritorio

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.

Habilidades que desarrollarás

Natural Language ProcessingDeep LearningMachine LearningTensorflowkeras

Aprende paso a paso

En un video que se reproduce en una pantalla dividida con tu área de trabajo, tu instructor te guiará en cada paso:

  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

Cómo funcionan los proyectos guiados

Tu espacio de trabajo es un escritorio virtual directamente en tu navegador, no requiere descarga.

En un video de pantalla dividida, tu instructor te guía paso a paso

Preguntas Frecuentes

Preguntas Frecuentes

¿Tienes más preguntas? Visita el Centro de Ayuda al Alumno.