AutoML 学习

目录

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背景

最近学习ML，NLP，DL ,发现有自动写代码（gan 目前只能算法生成，java 有可视化的模版生成），自动写诗（ gan），自动神经网络结构（google io） 等。兴奋，想想，如有一个能总结一些规律的，模式化过程，大神门经验的ML框架，不用每个人从头学习，经验积累（占用大部分时间），能有更多的时间，投入到高的角度去思考创造（相对）。忽然遇到一篇文章，正如所想， good…(一个懒惰的码农)

简介

What is AutoML?

Machine learning (ML) has achieved considerable successes in recent years and an ever-growing number of disciplines rely on it. However, this success crucially relies on human machine learning experts to perform the following tasks:

Preprocess the data
Select appropriate features
Select an appropriate model family
Optimize model hyperparameters
Postprocess machine learning models
Critically analyze the results obtained.

As the complexity of these tasks is often beyond non-ML-experts, the rapid growth of machine learning applications has created a demand for off-the-shelf machine learning methods that can be used easily and without expert knowledge. We call the resulting research area that targets progressive automation of machine learning AutoML.
Although it focuses on end users without expert ML knowledge, AutoML also offers new tools to machine learning experts, for example to:

Perform architecture search over deep representations
Analyse the importance of hyperparameters.

比赛

比赛名称 起止时间 资源 ChaLearn Automatic Machine Learning Challenge Dec. 8, 2014, midnight UTC—June 25, 2016, midnight UTC – slides paper site

相关文章

• Approaching (Almost) Any Machine Learning Problem | Abhishek Thakur | Pulse | LinkedIn 原文 译文

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