Generate Text Samples

This project is part of the Training Models on Imbalanced Text Data bundle.
prerequisites
intermediate Python • basics of NumPy, pandas, Jupyter, Google Colab notebooks, TensorFlow, and NLP
skills learned
building and training a deep learning model for text classification • using sklearn module to report model classification metrics • condition based sampling technique for NumPy array
KC Tung
1 week · 4-7 hours per week · ADVANCED
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liveProject This project is part of the Training Models on Imbalanced Text Data bundle. liveProjects give you the opportunity to learn new skills by completing real-world challenges in your local development environment. Solve practical problems, write working code, and analyze real data—with liveProject, you learn by doing. These self-paced projects also come with full liveBook access to select books for 90 days plus permanent access to other select Manning products. $19.99 $29.99 you save: $10 (33%)
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In this liveProject, you’ll build a deep learning model that can generate text in order to create synthetic training data. You’ll establish a data training set of positive movie reviews, and then create a model that can generate text based on the data. This approach is the basis of data augmentation.
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 training text generation. 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 notebooks
  • Basics of TensorFlow
TECHNIQUES
  • Basics of NLP
  • Basics of deep learning

you will learn

In this liveProject, you’ll learn how to generate synthetic training data for the purpose of data augmentation. This practice is exceedingly valuable for balancing datasets, and ensuring model accuracy with limited training materials.

  • Performing tokenization of training data
  • Manipulating text into format suitable for training a text generation model
  • Building a recurrent neural network to generate textfication metrics

features

Self-paced
You choose the schedule and decide how much time to invest as you build your project.
Project roadmap
Each project is divided into several achievable steps.
Get Help
While within the liveProject platform, get help from other participants and our expert mentors.
Compare with others
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book resources
Get full access to select books for 90 days. Permanent access to excerpts from Manning products are also included, as well as references to other resources.
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