Machine Learning-Algorithm Engineer-interview/written preparation-important knowledge point carding _ machine learning

Original address: http://blog.csdn.net/lrs1353281004/article/details/79529818

Sorting out the machine learning-algorithm engineers need to master the basic knowledge of machine learning, and attached to the internet I think that write a better blog address for reference. (Continuous update) machine learning-related basic concepts variance (variance) and bias (deviation)

https://www.zhihu.com/question/27068705 Common Performance Index

http://blog.csdn.net/lrs1353281004/article/details/79411552 generation model and discriminant model

https://www.cnblogs.com/zeze/p/7047630.html Integrated Learning: Bagging, boosting, stacking

https://www.sohu.com/a/167812554_465975

Https://www.cnblogs.com/liuwu265/p/4690486.html

http://blog.csdn.net/lrs1353281004/article/details/79520154 Logistic Regression

http://blog.csdn.net/feilong_csdn/article/details/64128443 gbdt (gradient ascending tree), Xgboost

Https://www.cnblogs.com/pinard/p/6140514.html
https://www.zhihu.com/question/41354392 SVM and Perceptual machine

Basic concept and principle of perception machine
http://blog.csdn.net/dream_angel_z/article/details/48915561
SVM Machine learning Interview Related Topics
http://blog.csdn.net/szlcw1/article/details/52259668 Naïve Bayes (naive Bayesian)

Principle derivation
http://blog.csdn.net/lrs1353281004/article/details/79437016
Principle and Application
http://blog.csdn.net/tanhongguang1/article/details/45016421
Instance
http://blog.csdn.net/fisherming/article/details/79509025 gradient Descent Method and Newton method

http://blog.csdn.net/lipengcn/article/details/52698895 Common Clustering method

http://blog.csdn.net/alex_luodazhi/article/details/47125149 supervised learning, unsupervised learning and semi-supervised learning

Regularization of http://blog.csdn.net/haishu_zheng/article/details/77927525 L1 and regularization of L2

http://blog.csdn.net/jinping_shi/article/details/52433975 Empirical Risk minimization (ERM) and structural risk minimization (SRM)

Http://blog.csdn.net/zhzhx1204/article/details/70163099?utm_source=itdadao&utm_medium=referral Maximum likelihood estimation (MLE) and maximal posteriori probability estimation (MAP)

http://blog.csdn.net/lin360580306/article/details/51289543
https://www.cnblogs.com/sylvanas2012/p/5058065.html Migration Learning

https://www.zhihu.com/question/41979241 Intensive Learning

http://blog.csdn.net/aliceyangxi1987/article/details/73327378 LDA, PCA

https://www.cnblogs.com/pinard/p/6244265.html deep Learning related neural networks (reverse propagation, gradient disappearance, dropout)

CS231N Course notes translation: reverse-propagating notes

Https://zhuanlan.zhihu.com/p/21407711?refer=intelligentunit

Gradient disappearance and gradient explosion
Http://blog.sina.com.cn/s/blog_6e32babb0102y1om.html
http://blog.csdn.net/qq_25737169/article/details/78847691
Dropout
http://blog.csdn.net/stdcoutzyx/article/details/49022443 CNN

Https://zhuanlan.zhihu.com/p/22038289?refer=intelligentunit RNN, Lstm

http://blog.csdn.net/hjimce/article/details/49095371
http://lib.csdn.net/article/deeplearning/45510 GAN

Http://36kr.com/p/5086889.html
https://www.leiphone.com/news/201701/Kq6FvnjgbKK8Lh8N.html