An Introduction to Statistical Learning with Applications in R - Gareth J.et al. Python Machine Learning- Sebastian Raschka Programming Collective Intelligence (集体编程智慧) - Toby Segaran 机器学习 - 周志华 统计学习方法 - 李航 最近我阅读了上面的书籍,想和大家分享一下我的主观评价。在每本书的总评...
[《An Introduction to Statistical Learning》的主要内容是什么?] 该书的主要内容涵盖了从基础概念到机器学习算法的广泛应用。它的主要章节包括: 1.线性回归:介绍了最简单的统计学习算法之一,线性回归。它解释了如何使用线性回归来建立一个模型,并使用最小二乘法来估计模型参数。 2.分类:介绍了分类问题和一些常用的...
ISLR - An Introduction to Statistical Learning with Applications in R 程序员百科书 斯坦福【统计学习导论】三位统计学习大师带你一起啃透《统计学习导论》这本书,带你一起了解机器学习算法全貌!简直不要太详细了!!!-统计学习/斯坦福/人工智能 小微带你学AI ...
【英语一小时】译读 An Introduction to Statistical Learning(1) 小善乄 【英语一小时】译读 An Introduction to Statistical Learning(5) 小善乄 小善乄 1:06:48 【英语一小时】译读 An Introduction to Statistical Learning(2) 小善乄 【英语一小时】译读 An Introduction to Statistical Learning(3) ...
Statistical learning is a branch of machine learning that is concerned with the statistical aspects of data analysis by means of machine learning algorithms. In the following, we present a leisurely introduction to this topic, as it is of particular interest for applications in engineering research ...
An Introduction to Statistical Learning provides an accessible overview of the field of statistical learning, an essential toolset for making sense of the vast and complex data sets that have emerged in fields ranging from biology to finance to marketing to astrophysics in the past twenty years. Th...
1 Introduction tools for understanding data tools can be classified as?supervised?or?unsupervised supervised statistical learning : statistical model for predicting, or estimating, an?output?based on inputs. unsupervised statistical learning:? inputs but?no supervising output 介绍三个数据库, To provide...
an introduction to statistical learning python 摘要: I.统计学习简介 A.统计学习的定义 B.统计学习的重要性 II.Python 在统计学习中的应用 A.Python 的优势 B.Python 的统计学习库 III.统计学习的基本概念 A.数据集的表示 B.监督学习和无监督学习 C.模型的评估和选择 IV.常见的统计学习方法 A.线性回归 B...
Springer Texts in Statistics(共118册), 这套丛书还有 《Statistical Analysis of Financial Data in R》《An Introduction to Bayesian Analysis》《Large Sample Techniques for Statistics》《Applied Multivariate Analysis》《Design and Analysis of Experiments》 等。