【文件属性】：
文件名称：Stanford 机器学习 笔记
文件大小：27.64MB
文件格式：ZIP
更新时间：2022-05-15 03:52:17
stanfo 笔记 机器学习
Supervised learning
Let’s start by talking about a few examples of supervised learning problems.
Suppose we have a dataset giving the living areas and prices of 47 houses
from Portland, Oregon:
Linear Regression
To make our housing example more interesting, let’s consider a slightly richer
dataset in which we also know the number of bedrooms in each house
【文件预览】：
StanfordNotes
----cs229-notes7a.pdf(265KB)
----cs229-notes9.pdf(83KB)
----cs229-gaussian_processes.pdf(160KB)
----loss-functions.pdf(69KB)
----cs229-prob.pdf(286KB)
----cs229-linalg.pdf(200KB)
----cs229-cvxopt2.pdf(199KB)
----cs229-notes5.pdf(87KB)
----representer-function.pdf(377KB)
----error-analysis.pdf(329KB)
----cs229-linalg (1).pdf(200KB)
----cs229-notes7b.pdf(51KB)
----cs229-prob (1).pdf(286KB)
----hoeffding.pdf(85KB)
----cs229-notes1.pdf(236KB)
----cs229-notes13.pdf(226KB)
----ML-advice.pdf(313KB)
----cs229-notes10.pdf(70KB)
----cs229-notes12.pdf(167KB)
----cs229-notes4.pdf(110KB)
----cs229-mt-review.pdf(2.47MB)
----gaussians.pdf(335KB)
----cs229-notes3.pdf(193KB)
----ESLII.pdf(20.64MB)
----more_on_gaussians.pdf(117KB)
----cs229-hmm.pdf(198KB)
----cs229-notes8.pdf(80KB)
----cs229-cvxopt.pdf(165KB)
----cs229-notes-backprop.pdf(148KB)
----cs229-notes-deep_learning.pdf(334KB)
----cs229-notes11.pdf(76KB)
----boosting.pdf(126KB)
----cs229-notes6.pdf(51KB)
----cs229-notes2.pdf(865KB)