摘要： Here a list of resources, mostly in the form of tutorials, covering most important topics in data science: This resource is part of a series on specific topics related to data science: regression, clustering, neural networks, deep learning, Hadoop, decision trees, ensembles, correlation, outliers, regression, Python, R, Tensorflow, SVM, data reduction, feature selection, experimental design, time series, cross-validation, model fitting, dataviz, AI and many more.
摘要： 近日，有越來越多的學者正在探討機器學習（和深度學習）的侷限性，並試圖爲人工智能的未來探路，紐約大學教授 Gary Marcus 就對深度學習展開了系統性的批判。此前，圖靈獎獲得者，UCLA 教授 Judea Pearl 題爲《Theoretical Impediments to Machine Learning with Seven Sparks from the Causal Revolution》的論文中，作者就已探討了當前機器學習存在的理論侷限性，並給出了面向解決這些問題，來自因果推理的七個啓發。Pearl 教授在 NIPS 2017 系列活動中對本文進行了討論，隨後，他也對一些人們關心的問題進行了解答。
