《Machine Learning for Designers》解構腦圖

導讀：如下是《Machine learning for Designers》的解構腦圖，原書2016年於OREILLY首次出版。作者Patrick Hebron是紐約大學交互通信項目（ITP）的特聘教授，專註於機器學習、人工智慧、計算機視覺等等領域的應用性研究。

原書電子版及腦圖下載

百度雲: https://pan.baidu.com/s/1eSzhXM6 密碼: c98x

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線上課程

「Machine Learning for Musicians and Artists」 taught by Rebecca Fiebrink:

「Machine Learning」 taught by Andrew Ng:

「Neural Networks for Machine Learning」 taught by Geoffrey Hinton:

機器學習 API

IBM Watson: IBM Watson

Amazon Machine Learning: Amazon Machine Learning - Predictive Analytics with AWS

Google Prediction API: https://cloud.google.com/prediction

Microsoft Azure: Directory of Azure Cloud Services | Microsoft Azure

BigML: BigML is Machine Learning made easy

ClarifAI: Image & Video Recognition API

開源機器學習工具

TensorFlow (C++, Python): https://www.tensorflow.org

Torch (C, Lua): Torch | Scientific computing for LuaJIT.

Caffe (C++): Caffe | Deep Learning Framework

cuDNN (C++, CUDA): NVIDIA cuDNN

Theano (Python): Welcome - Theano 0.9.0 documentation

Scikit-learn (Python): http://scikit-learn.org

Shogun (C++, Python, Java, Lua, others): http://www.shoguntoolbox.org

Spark MLlib (Python, Java, Scala): MLlib | Apache Spark

Deeplearning4j (Java, Scala): Open-source, Distributed Deep Learning for the JVM

數據集

UCI Machine Learning Repository: UCI Machine Learning Repository

MNIST Database of Handwritten Digits: Yann LeCuns Home Page

CIFAR Labeled Image Datasets: Alex Krizhevsky

ImageNet Image Database: http://www.image-net.org

Microsoft Common Objects in Context: Common Objects in Context

編輯：魏啟龍 尹青

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