Imbalanced Text Data

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This project is part of the liveProject series Training Models on Imbalanced Text Data
prerequisites
intermediate Python • basics of NumPy, pandas, and Jupyter Notebook
skills learned
use a dictionary to decode and encode data • learn NumPy array indexing techniques • understand Python dictionary data structure, and how to edit and manipulate it
KC Tung
1 week · 4-7 hours per week · ADVANCED
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Look inside
In this liveProject, you’ll explore a dataset of movie reviews and prepare it for sentiment analysis. The dataset you've provided is balanced between positive and negative reviews, but is encoded in such a way that you will need to use the dictionary (lookup) in this dataset package to decode the content to plain text. Your challenges will include decoding the data to plain text, and then converting the plain text into tokens in a Pythonic manner.
This project is designed for learning purposes and is not a complete, production-ready application or solution.

book resources

When you start your liveProject, you get full access to the following books for 90 days.

project author

KC Tung
KC Tung is an AI architect, machine learning engineer, and data scientist who specializes in delivering AI, deep learning, and NLP models across enterprise architectures. As an AI architect at Microsoft, he helps enterprise customers with use-case driven architecture, AI/ML model development/deployment in the cloud, and technology selection and integration best suited for their requirements. He is a Microsoft certified AI engineer and data engineer. He has a PhD in molecular biophysics from the University of Texas Southwestern Medical, and has spoken at the 2018 O'Reilly AI Conference in San Francisco and the 2019 O'Reilly Tensorflow World Conference in San Jose.

prerequisites

This liveProject is for Python programmers interested in common tools for encoding data for NLP. To begin this liveProject, you will need to be familiar with:

TOOLS
  • Intermediate Python, with basics of NumPy and pandas
  • Basics of Jupyter Notebook
  • Basics of Google Colab notebook
  • Basics of TensorFlow
TECHNIQUES
  • Basics of NLP
  • Basics of deep learning

you will learn

In this liveProject, you’ll learn the basics of encoding and decoding techniques. These are common techniques for solving natural language processing (NLP) problems.

  • Use tf.keras.datasets module for accessing IMDb movie review dataset
  • Learn NumPy array indexing techniques
  • Understand Python dictionary data structure, and how to edit and manipulate it
  • Use a dictionary to decode and encode data

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