只对该包做一个简单的介绍和使用方法的查找，具体可以查看官方文档，使用的时候查找即可 简介 scikit-learn sklearn是一个Python第三方提供的非常强力

这几天看吴恩达深度学习作业时候，遇到了np.dot()、np.outer()、np.multiply()、*几个函数，记录一下 np.dot 1.如果处理

问题陈述 问题陈述： Suppose you are starting a company that grows and sells wild mushrooms. Since not all mushrooms are edible, you’d like to be able to tell whether a given mushroom is edible or poisonous based on it’s physical attributes You have some existing data that you can use for this task. Can you use the data to help you identify which mushrooms

本文主要参考别人的文章加入自己的话来帮助自己的理解，非原创哦 最近在学Andrew的Machine Learning课程，在学习欠拟合（unde

不带正则的 问题描述 Suppose that you are the administrator of a university department and you want to determine each applicant’s chance of admission based on their results on two exams. You have historical data from previous applicants that you can use as a training set for logistic regression. For each training example, you have

逻辑回归 实际上用于分类问题中（不要被名字迷惑），其输出值在0-1之间 这里采用sigmoid作为model，公式如下： $g(z)=\frac{1}{1+e^{-z}}$ model： $f(\vec{w},b)(\vec{x}) = g(\vec{w}\cdot{\vec{x}}+b) = \frac{1}{1+e^{-(\vec{w}\cdot{\vec{x}}+b)}}$