There are 6 repositories under statistics-learning topic.
📒《统计学习方法-李航》学习笔记 200 页 PDF,各种手推公式细节讲解,包含详细的目录以及R语言代码实现,可结合《统计学习方法》提高学习效率,适合机器学习、深度学习初学者。
Pluto notebooks accompanying the book Statistics With Julia (https://statisticswithjulia.org).
R Code Examples for Data Analytics
A 12 week intensive course about Python and data science.
Introductory Statistics for Economists (Undergraduate Intro Course)
Introduction to Statistics: an integrated textbook and workbook using R
快速计算商旅轨迹 非线性坐标数据分析
Some materials from my "Introduction to Statistics and EEG Analysis" course, taught in weekly lab meetings.
Official Implementation of On Optimal Private Online Stochastic Optimization and High Dimensional Decision Making
DataScience
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.
Statistics is a vital foundation for data science and machine learning, offering insights into data behavior through probability, distributions, and key analyses like T Test and Chi-Square.
Statistics Learning Course by JunZhu
Notes for Statistics UN1101, Columbia University
Statistics Cheatsheets
MAT-243 Applied Statistics for STEM Notes
NLP - descriptive statistics of COCO annotations via Python COCO-API
A simple spam classifier using SVM with a linear kernel.
fstaple is a free, lightweight, and modern rewrite of stapplet.com.
Scripts and data from George Casella's Statistical Design
Some notes and codes in the process of learning machine learning | 机器学习基础算法的笔记和代码 | KNN (k近邻) | Linear Model (线性模型) | SVM (支持向量机) | Decision Tree (决策树)
Fundamentals of Data Analytics module. Assignment concerning Anscombe's quartet data set in Jupyter.
Interactive tutorials for "Introduction to The New Statistics" (ITNS) - WIP
QSD.OX.MATHS.OBSIDIAN
Statistical Analysis on the Views of Americans in the field of science and technology development in the distinct future.
R is a programming language and free software environment for statistical computing and graphics supported by the R Foundation for Statistical Computing. Sample exersies of R Programming for Machine learning for training an developmeny
Features are computed from a digitized image of a fine needle aspirate (FNA) of a breast mass. They describe characteristics of the cell nuclei present in the image.
Formula Sheet for Ph.D Qualifying Exams in Probability and Stochastic Processes