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Machine Learning API

ICDSS Machine Learning Workshop Series: Machine Learning API

Getting Started

macOS

  1. source scripts/setup.sh

Prerequisites

  • Linear Models
  • Scientific Python (NumPy & SciPy)
  • Neural Networks

Overview

In this workshop we will cover the most frequently used High-Level Machine Learning libraries, scikit-learn and keras. The focus of this workshop will be on how to the implementation of abstract models in code, using the universal fit-predict-score pattern most machine learning APIs follow. Multiple sandbox projects will be attempted, including multivariate regression, classification and time-series forecasting.

License

MIT License

Copyright (c) 2018 ICDSS

Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.

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ICDSS Machine Learning Workshop Series: Machine Learning APIs

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