book 12
这本书应该是机械学习 Machine Learning 的兰亭集序!
早期的 Nips Conference 群英荟萃,华山论剑!去的都是鸿儒!谈笑的都是先贤!!!
不管是现在流行的 kaggle, coursea, udacity, udemy, mooc ….. 这些创始人
书本上的 Van Nuvemann, Shannon, Hardy , Number theory professor…
外星人 Elon mask.
最惊喜的是有babara , 我超喜欢她的learning how to learning.
我们的qualify 是take home exam, more of how you see / approach problems rather than have a definite solution for it.
感觉把这本书搞懂了就qualify 随便写,随便过!
Machine Learning 可以分三个大方向, Deep Learning , CNN neutral network 那一套, Forecasting (model prediction), NLP, Natural Language Process.
这本书为了qualify 肯定要反复读的,书里面提到过的modeling, 我把我学过的总结一下。
但现在不全,等以后再慢慢补全吧。
zSVM support vector machine: able to classify, but won’t be able to show the exact support vector coefficients.
Gradient Boost
Gradient Descent(作者超喜欢!)
Bayesian
Continuous function/ Spike
reinforcement learning: future rewards
who processes the most data wins. Of course the winner is China.
every night I pray, dear Lord, let the equation be linear, noise be Gaussian , and the variables be seprable.
小时候不觉得这个Log 有什么好? 现在知道她妙在能 separate variables.
化繁为简, 乘除都变成加减!
*Note : 书里有好多地方提到了Go, Alpha Go, 但都是韩国的…
想棋魂了,想光亮双子星,楚赢, 方旭….. all the crew