Machine Learning Engineering Tutorial
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An Machine Learning Engineering Tutorial is an engineering tutorial on how to build ML-based applications (with ML techniques and ML tools).
- Example(s):
- Counter-Example(s):
- Machine Learning Course.
- a Data Science Tutorial (which likely includes data munging and likely excludes ML model deployment topics)
- See: Applied Natural Language Processing Tutorial.
References
2017
- Adam Geitgey. (2017). "Value Estimation (with Python)"
2016
- "Machine Learning with scikit-learn".
- QUOTE: This tutorial aims to provide an introduction to machine learning and scikit-learn "from the ground up". We will start with core concepts of machine learning, some example uses of machine learning, and how to implement them using scikit-learn. Going in detail through the characteristics of several methods, we will discuss how to pick an algorithm for your application, how to set its parameters, and how to evaluate performance.
- Part-1: http://youtube.com/watch?v=OB1reY6IX-o
- Part-2: http://youtube.com/watch?v=Cte8FYCpylk
- repo: http://github.com/amueller/scipy-2016-sklearn