Deploy a Predictor on Android

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prerequisites
basics of Python, TensorFlow, Keras, and Android development
skills learned
Converting a model to Android use • generating JavaScript usable data sets • simple Android development
Evan Hennis
1 week · 4-6 hours per week · INTERMEDIATE
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catalog / Data Science
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Look inside
In this liveProject, you’ll create an Android application that can run a pretrained basketball predictor deep learning model for the easy use of your client. Your challenges will include converting the DataFrames into JavaScript arrays, converting your model into a TensorFlow Lite model, and finally packaging the model inside a working Android application.
This project is designed for learning purposes and is not a complete, production-ready application or solution.

project author

Evan Hennis
Evan Hennis is a Google Developer Expert in Machine Learning and an international speaker. He has an undergraduate degree in Computer Science from Iowa State University and a Master's degree in Computer Science with a specialization in machine learning from Georgia Tech. He has spent over sixteen years in software development, working across multiple languages and domains.

prerequisites

This project is for intermediate Python programmers or Android developers trying to add some data science to their applications looking to enhance their data science skills with deep learning techniques. To begin this liveProject, you will need to be familiar with:

TOOLS
  • Basics of Python
  • Basics of pandas
  • Basics of Google Colab
  • Basics of TensorFlow and Keras
    • TECHNIQUES
    • Basics of machine learning
    • Basics of Android development

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  • choose twelve free products per year
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