/tweet-emotion-recognition

Coursera's guided project for tweet emotion recognition using TensorFlow

Primary LanguageJupyter NotebookMIT LicenseMIT

Tweet Emotion Recognition using TensorFlow1

Welcome to Tweet Emotion Recognition with TensorFlow This is a project-based course which should take less than 2 hours to finish. Before diving into the project, please take a look at the course objectives and structure:

Course Objectives

In this course, we will focus on the following objectives:

  1. Using a Tokenizer in TensorFlow
  2. Padding and Truncating Sequences
  3. Creating and Training Recurrent Neural Networks
  4. Using NLP and Deep Learning to perform Text Classification

Course Structure

This course is divided into 3 parts:

  1. Course Overview: This introductory reading material.
  2. Tweet Emotion Recognition with TensorFlow: This is the hands on project that we will work on in Rhyme.
  3. Graded Quiz: This is the final assignment that you need to pass in order to finish the course successfully.

Project Structure

The hands on project on Tweet Emotion Recognition with TensorFlow is divided into following tasks:

  • Task 1: Introduction
  • Task 2: Setup and Imports
  • Task 3: Importing Data
  • Task 4: Tokenizer
  • Task 5: Padding and Truncating Sequences
  • Task 6: Preparing Labels
  • Task 7: Creating the Model
  • Task 8: Training the Model
  • Task 9: Evaluating the Model

Footnotes

  1. This hands-on course is provided by Coursera ↩