一开始对于机器学习,主要是有监督学习,我的看法是: 假定一个算法模型,然后它有一些超参数,通过喂多组数据,每次喂数据后计算一下这些超参数.最后,数据喂完了,参数取值也就得到了.这组参数取值+这个算法,就是模型文件,后续能够用来预测,也就是直接用这个算法+这个参数取值的组合,能投入实际使用,做分类/回归. 但是后来出现了inference,以及指出和learning是不同的过程.这就有点让人发晕了.learning是啥?inference是啥?learning不是inference的一种吗? 好吧…

昨天总结了深度学习的资料,今天把机器学习的资料也总结一下(友情提示:有些网站需要"科学上网"^_^) 推荐几本好书: 1.Pattern Recognition and Machine Learning (by Hastie, Tibshirani, and Friedman's ) 2.Elements of Statistical Learning(by Bishop's) 这两本是英文的,但是非常全,第一本需要有一定的数学基础,第可以先看第二本.如果看英文觉得吃力,推荐看一下下面…

最近在学深度学习相关的东西,在网上搜集到了一些不错的资料,现在汇总一下: Free Online Books  by Yoshua Bengio, Ian Goodfellow and Aaron Courville Neural Networks and Deep Learning42 by Michael Nielsen Deep Learning27 by Microsoft Research Deep Learning Tutorial23 by LISA lab, University…

Candidate Elimination Thanks for Sanketh Vedula. This is a good demo to understand candidate elimination algorithm that I have optimized based on this guy's good work. rika@rika-UX303UB$ ./a.out <Input> Number of Features: <Input> Number of At…

Machine and Deep Learning with Python Education Tutorials and courses Supervised learning superstitions cheat sheet Introduction to Deep Learning with Python How to implement a neural network How to build and run your first deep learning network Neur…

##机器学习(Machine Learning)&深度学习(Deep Learning)资料(Chapter 2)---#####注:机器学习资料[篇目一](https://github.com/ty4z2008/Qix/blob/master/dl.md)共500条,[篇目二](https://github.com/ty4z2008/Qix/blob/master/dl2.md)开始更新------#####希望转载的朋友**一定要保留原文链接**,因为这个项目还在继续也在不定期更新．希望看到…

https://www.quora.com/How-do-I-learn-machine-learning-1?redirected_qid=6578644   How Can I Learn X? Learning Machine Learning Learning About Computer Science Educational Resources Advice Artificial Intelligence How-to Question Learning New Things Lea…

https://www.quora.com/How-do-I-learn-mathematics-for-machine-learning   How do I learn mathematics for machine learning? Promoted by Time Doctor Software for productivity tracking. Time tracking and productivity improvement software with screenshots…

ICLR 2013 International Conference on Learning Representations May 02 - 04, 2013, Scottsdale, Arizona, USA ICLR 2013 Workshop Track Accepted for Oral Presentation Zero-Shot Learning Through Cross-Modal Transfer Richard Socher, Milind Ganjoo, Hamsa Sr…

Problems[show] Classification Clustering Regression Anomaly detection Association rules Reinforcement learning Structured prediction Feature engineering Feature learning Online learning Semi-supervised learning Unsupervised learning Learning to rank…