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Madison J Myers edited this page Dec 13, 2017
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This pattern will guide you through downloading your data, installing Tensorflow and Keras and training a deep learning language model.
Conduct a data science pipeline of building a Recurrent Neural Network (RNN) in a notebook, using Keras and Tensorflow.
Cognitive & Data Analytics
add intro here
Madison J. Myers https://www.linkedin.com/in/madisonjmyers/
Jeremy Nixon
https://github.com/MadisonJMyers/Training-a-Deep-Learning-Language-Model-Using-Keras-and-Tensorflow
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.
- 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.
- 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.
TBD
- 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.