AI/Machine Learning Book List

多啲上線性啟示錄,
學到lda, pca, svd, spectral decomposition, cholesky factorization, covariance matrix, laplacian graph, matrix differentiation, schur complement等就夠
仲要識得用向量, hessian, laplacian矩陣表示quadratic, gaussian, talyor

Iq唔過100 係唔係應該唔好浪費時間

建議連連登都唔好上

只係覺得呢行都幾大risk 最唔到research個part
好似無咩作為

我仲讀緊書 cu ie
遲d得揀theme 而其中一個係AI

覺得自己天資一般 但有興趣

岩, 有興趣先支持到落去,
但智力連100(正常人水平)都冇建議放棄, 雖然我知你講笑

可以向 practical 方向發展，好似你要渣車，都唔駛一定要識整車啦。

如果fyp想玩ml (practical) 呢2本夠唔夠做? 會唔會太皮毛?

https://doc.lagout.org/science/Artificial%20Intelligence/Machine%20learning/Machine%20Learning_%20An%20Algorithmic%20Perspective%20%282nd%20ed.%29%20%5BMarsland%202014-10-08%5D.pdf

http://neuralnetworksanddeeplearning.com/index.html

見2本都有d python example睇下
未確實諗到想做咩topic, 睇書嗰陣順便攞下靈感

想問下成本磚咁厚既書係咪真係粒粒字睇哂
定有咩速讀方法

有數學基礎自然睇得明
BTW 我睇大陸本西瓜書同李航本野

一本書起碼都幾百頁紙 睇得明都都有排睇

想速讀咪睇youtube 啲tutorial, lecture

咁巴打有book list嘛
想知讀書的話點樣先最effective

堆書本身係for master PhD students/researchers睇，人地正職就係做research睇書學野
如果你做緊野自學一定冇咁多時間

入門可以睇依度
https://github.com/jindongwang/MachineLearning

笑左 今時今日應該唔會iq唔過100
你想叫你呀媽學ml呀？