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Using Deep Learning to Generate Restaurant Reviews

This pattern will guide you through downloading data, installing Tensorflow and Keras, and training a deep learning language model.

Short Description

Conduct a data science pipeline of building a Recurrent Neural Network (RNN) in a notebook, using Keras and Tensorflow.

Offering Type

Cognitive & Data Analytics

Introduction

add intro here

Author

• Madison J. Myers
• Jeremy Nixon

Code

https://github.com/IBM/deep-learning-language-model

Overview

The user will learn:

• How to use Keras.
• How to use Tensorflow.
• How to use a Jupyter Notebook.
• How to create a Recurrent Neural Network (RNN) language model.
• How to apply this to other areas..

This journey was created for data scientists and data lovers who are interested in deep learning and fraud detection and/or those who are new to Deep Learning or Keras. This will guide the user through a text generating pipeline.

Link to architecture diagram:

Included Components

• Jupyter Notebook: An open source web application that allows you to create and share documents that contain live code, equations, visualizations, and explanatory text.
• Keras: The Python Deep Learning library.
• Tensorflow: An open-source software library for Machine Intelligence.

Featured technologies

• Cloud: Accessing computer and information technology resources through the Internet.
• Data Science: Systems and scientific methods to analyze structured and unstructured data in order to extract knowledge and insights.
• Python: Python is a programming language that lets you work more quickly and integrate your systems more effectively.

Blog

TBD

Links

• Create Data Science Experience Notebooks
• Jupyter Notebook: An open source web application that allows you to create and share documents that contain live code, equations, visualizations, and explanatory text.
• Keras: The Python Deep Learning library.
• Tensorflow: An open-source software library for Machine Intelligence.