└── README.md /README.md: -------------------------------------------------------------------------------- 1 | # awesome online books 2 | 3 | ## Statistics 4 | 5 | https://jbhender.github.io/Stats506/F18/index.html 6 | Stats 506, Computational Methods and Tools in Statistics 7 | Instructor: James Henderson, PhD 8 | Fall 2018 9 | 10 | https://otexts.org/fpp2/ 11 | Forecasting: Principles and Practice, Rob J Hyndman and George Athanasopoulos 12 | 13 | http://r4ds.had.co.nz/ 14 | R for Data Science 15 | Garrett Grolemund 16 | Hadley Wickham 17 | 18 | https://adv-r.hadley.nz/ 19 | Advanced R 20 | Hadley Wickham 21 | 22 | https://www.tidytextmining.com/ 23 | Text Mining with R 24 | A Tidy Approach 25 | Julia Silge and David Robinson 26 | 2018-04-02 (last update) 27 | 28 | https://nbviewer.jupyter.org/github/CamDavidsonPilon/Probabilistic-Programming-and-Bayesian-Methods-for-Hackers/tree/master/ 29 | 30 | https://nbviewer.jupyter.org/github/ptwobrussell/Mining-the-Social-Web-2nd-Edition/tree/master/ipynb/ 31 | 32 | https://nbviewer.jupyter.org/github/unpingco/Python-for-Signal-Processing/tree/master/ 33 | 34 | https://bookdown.org/ 35 | 36 | http://www.burns-stat.com/documents/books/the-r-inferno/ 37 | 38 | https://rud.is/books/21-recipes/ 39 | 40 | http://www.burns-stat.com/documents/tutorials/impatient-r/ 41 | 42 | https://rud.is/books/drill-sergeant-rstats/ 43 | 44 | https://rud.is/books/creating-ggplot2-extensions/ 45 | 46 | http://a-little-book-of-r-for-time-series.readthedocs.io/en/latest/index.html 47 | 48 | https://lectures.quantecon.org/py/index.html 49 | 50 | https://www.kevinsheppard.com/teaching/python/notes/ 51 | 52 | http://moderndive.netlify.com/6-regression.html 53 | 54 | http://style.tidyverse.org/ 55 | 56 | http://www.r2d3.us/ 57 | 58 | http://r-pkgs.had.co.nz/ 59 | 60 | http://www.gastonsanchez.com/r4strings/ 61 | 62 | https://mml-book.github.io/ 63 | 64 | https://www.econometrics-with-r.org/ 65 | 66 | http://www-math.bgsu.edu/~albert/bcwr/ 67 | 68 | http://statmath.wu-wien.ac.at/~zeileis/teaching/AER/ 69 | 70 | https://cengel.github.io/R-data-wrangling/index.html 71 | 72 | https://little-book-of-r-for-multivariate-analysis.readthedocs.io/en/latest/index.html 73 | 74 | https://developers.google.com/machine-learning/crash-course/prereqs-and-prework 75 | 76 | https://www.ime.unicamp.br/~cnaber/Ensino.htm 77 | 78 | https://bookdown.org/yihui/rmarkdown/ 79 | 80 | https://principles.tidyverse.org/ 81 | 82 | https://advanced-r-solutions.rbind.io/ 83 | 84 | https://rc2e.com 85 | 86 | http://cs231n.github.io/ 87 | 88 | http://www.feat.engineering/ 89 | 90 | http://neuralnetworksanddeeplearning.com/ 91 | 92 | https://christophm.github.io/interpretable-ml-book/ 93 | 94 | https://therinspark.com/ 95 | 96 | https://bookdown.org/ccolonescu/RPoE4/ 97 | 98 | https://smac-group.github.io/ts/ 99 | 100 | https://www.ssc.wisc.edu/~bhansen/econometrics/Econometrics.pdf 101 | 102 | https://jakevdp.github.io/PythonDataScienceHandbook/index.html 103 | 104 | http://www.mlfactor.com/ 105 | 106 | http://sillasgonzaga.com/material/cdr/ 107 | 108 | https://material.curso-r.com/ 109 | 110 | https://www.math.nyu.edu/faculty/avellane/ 111 | 112 | http://www.stat.columbia.edu/~gelman/book/ 113 | 114 | ##### Patrick Landreman: A Crash Course in Applied Linear Algebra | PyData New York 2019 115 | 116 | - https://www.youtube.com/watch?v=wkxgZirbCr4 117 | - https://github.com/plandrem/PyData-2019 118 | - http://vmls-book.stanford.edu/ 119 | - http://ee263.stanford.edu/ 120 | - https://www.youtube.com/playlist?list=PL06960BA52D0DB32B 121 | 122 | 123 | ##### Stanford CS229: Machine Learning | Autumn 2018 124 | 125 | - https://www.youtube.com/playlist?list=PLoROMvodv4rMiGQp3WXShtMGgzqpfVfbU 126 | - http://cs229.stanford.edu/syllabus-autumn2018.html?utm_campaign=Data_Elixir&utm_source=Data_Elixir_283 127 | 128 | 129 | #### Practical Python Programming 130 | 131 | - https://dabeaz-course.github.io/practical-python/ 132 | 133 | 134 | #### Introductory Econometrics for Finance 135 | 136 | - Code & Datasets: 137 | - Python: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3475303 138 | - R: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3466882 139 | 140 | #### Topics in Mathematics with Applications in Finance 141 | 142 | - https://ocw.mit.edu/courses/mathematics/18-s096-topics-in-mathematics-with-applications-in-finance-fall-2013/index.htm 143 | 144 | - http://www.moving-averages.technicalanalysis.org.uk/ 145 | 146 | ### Financial Engineering Analytics: A Practice Manual Using R 147 | 148 | https://bookdown.org/wfoote01/faur/ 149 | 150 | ### Elements of Data Science 151 | 152 | https://allendowney.github.io/ElementsOfDataScience/index.html 153 | 154 | ### Causal Inference for The Brave and True 155 | 156 | https://matheusfacure.github.io/python-causality-handbook/landing-page.html 157 | 158 | ### The Shiny AWS Book 159 | 160 | https://business-science.github.io/shiny-production-with-aws-book/ 161 | 162 | ### Introduction to Computational Finance and Financial Econometrics with R 163 | 164 | https://bookdown.org/compfinezbook/introcompfinr/ 165 | 166 | ### YaRrr! The Pirate’s Guide to R 167 | 168 | https://bookdown.org/ndphillips/YaRrr/ 169 | 170 | 171 | ### Bayes Rules! An Introduction to Applied Bayesian Modeling 172 | 173 | https://www.bayesrulesbook.com/ 174 | 175 | 176 | ### Econometric Data Science: A Predictive Modeling Approach 177 | 178 | https://www.sas.upenn.edu/~fdiebold/Teaching104/Econometrics.pdf 179 | 180 | 181 | ### Tidy Modeling with R 182 | 183 | https://www.tmwr.org/ 184 | 185 | ### LINEAR ALGEBRA - MIT 186 | 187 | https://ocw.mit.edu/courses/18-06-linear-algebra-spring-2010/ 188 | 189 | ### 5min statistics 190 | 191 | https://stephens999.github.io/fiveMinuteStats/index.html 192 | 193 | ### Tidy Portfolio Management in R 194 | 195 | https://bookdown.org/sstoeckl/Tidy_Portfoliomanagement_in_R/ 196 | 197 | ### An Introduction to Bayesian Thinking 198 | 199 | https://statswithr.github.io/book/ 200 | 201 | ### The Derivatives Academy 202 | 203 | https://bookdown.org/maxime_debellefroid/MyBook/ 204 | --------------------------------------------------------------------------------