dsfb/online-books

A list of online book of my own interest

awesome online books

Statistics

https://otexts.org/fpp2/ Forecasting: Principles and Practice, Rob J Hyndman and George Athanasopoulos

http://r4ds.had.co.nz/ R for Data Science Garrett Grolemund Hadley Wickham

https://adv-r.hadley.nz/ Advanced R Hadley Wickham

https://www.tidytextmining.com/ Text Mining with R A Tidy Approach Julia Silge and David Robinson 2018-04-02 (last update)

https://nbviewer.jupyter.org/github/CamDavidsonPilon/Probabilistic-Programming-and-Bayesian-Methods-for-Hackers/tree/master/

https://nbviewer.jupyter.org/github/ptwobrussell/Mining-the-Social-Web-2nd-Edition/tree/master/ipynb/

https://nbviewer.jupyter.org/github/unpingco/Python-for-Signal-Processing/tree/master/

https://bookdown.org/

http://www.burns-stat.com/documents/books/the-r-inferno/

https://rud.is/books/21-recipes/

http://www.burns-stat.com/documents/tutorials/impatient-r/

https://rud.is/books/drill-sergeant-rstats/

https://rud.is/books/creating-ggplot2-extensions/

http://a-little-book-of-r-for-time-series.readthedocs.io/en/latest/index.html

https://lectures.quantecon.org/py/index.html

https://www.kevinsheppard.com/teaching/python/notes/

http://moderndive.netlify.com/6-regression.html

http://style.tidyverse.org/

http://www.r2d3.us/

http://r-pkgs.had.co.nz/

http://www.gastonsanchez.com/r4strings/

https://mml-book.github.io/

https://www.econometrics-with-r.org/

http://www-math.bgsu.edu/~albert/bcwr/

http://statmath.wu-wien.ac.at/~zeileis/teaching/AER/

https://cengel.github.io/R-data-wrangling/index.html

https://little-book-of-r-for-multivariate-analysis.readthedocs.io/en/latest/index.html

https://developers.google.com/machine-learning/crash-course/prereqs-and-prework

https://www.ime.unicamp.br/~cnaber/Ensino.htm

https://bookdown.org/yihui/rmarkdown/

https://principles.tidyverse.org/

https://advanced-r-solutions.rbind.io/

https://rc2e.com

http://cs231n.github.io/

http://www.feat.engineering/

http://neuralnetworksanddeeplearning.com/

https://christophm.github.io/interpretable-ml-book/

https://therinspark.com/

https://bookdown.org/ccolonescu/RPoE4/

https://smac-group.github.io/ts/

https://www.ssc.wisc.edu/~bhansen/econometrics/Econometrics.pdf

https://jakevdp.github.io/PythonDataScienceHandbook/index.html

http://www.mlfactor.com/

https://www.bayesrulesbook.com/

https://www.tmwr.org/

http://sillasgonzaga.com/material/cdr/

https://material.curso-r.com/

https://www.math.nyu.edu/faculty/avellane/

http://www.stat.columbia.edu/~gelman/book/

Patrick Landreman: A Crash Course in Applied Linear Algebra | PyData New York 2019

• https://www.youtube.com/watch?v=wkxgZirbCr4
• https://github.com/plandrem/PyData-2019
• http://vmls-book.stanford.edu/
• http://ee263.stanford.edu/
• https://www.youtube.com/playlist?list=PL06960BA52D0DB32B

Stanford CS229: Machine Learning | Autumn 2018

• https://www.youtube.com/playlist?list=PLoROMvodv4rMiGQp3WXShtMGgzqpfVfbU
• http://cs229.stanford.edu/syllabus-autumn2018.html?utm_campaign=Data_Elixir&utm_source=Data_Elixir_283

Practical Python Programming

• https://dabeaz-course.github.io/practical-python/

Introductory Econometrics for Finance

• Code & Datasets: https://www.cambridge.org/br/academic/subjects/economics/finance/introductory-econometrics-finance-4th-edition
• Python: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3475303
• R: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3466882

Topics in Mathematics with Applications in Finance

• https://ocw.mit.edu/courses/mathematics/18-s096-topics-in-mathematics-with-applications-in-finance-fall-2013/index.htm

• http://www.moving-averages.technicalanalysis.org.uk/

Financial Engineering Analytics: A Practice Manual Using R

https://bookdown.org/wfoote01/faur/