statistics-learning 开源项目推荐（103 个）

cfgranda /ps4ds

数据科学中的概率论与统计学：一套面向数据科学的自成体系的概率论与统计学入门材料，包括免费 PDF、使用 23 个真实数据集的 103 个 Python notebook、配有幻灯片的 118 个视频，以及 200 道练习的解答

xlite-dev /lihang-notes

📚《统计学习方法-李航: 笔记》 200页PDF，包含详细的公式细节讲解以及R语言实现 🎉

StatisticalRethinkingJulia /StatisticsWithJuliaPlutoNotebooks.jl

Pluto notebooks accompanying the book Statistics With Julia (https://statisticswithjulia.org).

kiat /R-Examples

R Code Examples for Data Analytics

lt-shy-john /python-data-analytics-course

A 12 week intensive course about Python and data science.

Lisp-Stat /IPS9

Examples from the book Introduction to the Practice of Statistics

NBISweden /workshop-mlbiostatistics

Geared towards life scientists wanting to be able to understand and use basic statistical and machine learning methods

VectorPosse /intro_stats

Introduction to Statistics: an integrated textbook and workbook using R

FanWangEcon /Stat4Econ

Introductory Statistics for Economists (Undergraduate Intro Course)

cogstat /cogstat

A simple to use statistical package.

vjcitn /CSHstats

R vignettes/pkgdown for elementary statistics for a summer course

Icelk /std-dev

Your Swiss Army knife for swiftly processing any amount of data.

hugoquene /QMS-EN

Textbook on Quantitative Methods and Statistics (English version, EN), available at https://hugoquene.github.io/QMS-EN/

zhengyu19921215 /AI-Algorithmic-Engineer-Manual

该项目在 GitHub 上没有填写描述

yaoguangluo /Data_Prediction

快速计算商旅轨迹 非线性坐标数据分析

ssghirripa /Stats-EEG-Tutorial

Some materials from my "Introduction to Statistics and EEG Analysis" course, taught in weekly lab meetings.

arsilva87 /statsbook

Estatística Decodificada (livro)

hugoquene /KMS-NL

tekstboek Kwantitatieve Methoden en Statistiek (Nederlandstalige versie, NL), beschikbaar via https://hugoquene.github.io/KMS-NL/

QSDQSB /OxMaths.obsidian

QSD.OX.MATHS.OBSIDIAN

suneelpatel /Statistics-for-Data-Science-using-R

Learn the core statistical concepts, followed by application of these concepts using R Studio with the a nice combination of theory and practice. Learn key statistical concepts and techniques like exploratory data analysis, correlation, regression, and inference.