Re: SciPy-User Digest, Vol 232, Issue 3
Kevin Dunn <[email protected]> Wed, 15 Feb 2023 20:47:51 +0100
| Newsgroups | gmane.comp.python.scientific.user |
|---|---|
| Message-ID | <CAGD7iRa8JzJrt0=qS9PC2q1yOp2x1rzvYs0Bjq+QSZkRW-1Z1w@mail.gmail.com> |
--===============0687874826537178394== Content-Type: multipart/alternative; boundary="000000000000b8a94905f4c25b19" --000000000000b8a94905f4c25b19 Content-Type: text/plain; charset="UTF-8" I am a bit biased of course, but my online book could also meet your needs. Process Improvement using Data. https://learnche.org/pid/ Chapter 4 is about Regression, chapter 2 on fundamental stats, and chapter 5 on designed experiments (including a full online course on Coursera). It's been a free, Creative Commons licensed resource since 2010, and used by quite a number of industrial companies and universities daily. I'm working on converting the R code to Python, so both are available side by side. The repo is available on GitHub if anyone is interested in helping speed that up ;) https://github.com/kgdunn/pid-book Kevin Date: Wed, 15 Feb 2023 12:42:48 -0500 > From: David Nicholson <[email protected]> > Subject: [SciPy-User] Re: Textbook Recommendations > To: SciPy Users List <[email protected]> > > fwiw, some books from the Executable Books gallery ( > https://executablebooks.org/en/latest/gallery/) > > https://gulinan.github.io/mat244e/ > http://theoryandpractice.org/stats-ds-book/intro.html > > See also this translating Danielle Navarro's Learning Stats with R to > Python: > https://ethanweed.github.io/pythonbook/landingpage.html > > David Nicholson, Ph.D. > https://nicholdav.info/ > https://github.com/NickleDave > > > On Wed, Feb 15, 2023 at 11:47 AM Albert Steppi <[email protected]> > wrote: > > > Hi Britta, > > > > I haven't read anything Python specific, but I like the following books: > > > > For basic introductory stats, Freedman, Pisani, and Purves > > <https://wwnorton.com/books/Statistics/> > > > > As a follow up, Freedman's Statistical Models: Theory and Practice > > < > https://www.cambridge.org/core/books/statistical-models/68F8872C7788AF62BD6513F7071EE1BA#fndtn-information > >, > > teaches one to think critically about regression modeling and its > > limitations. > > > > Efron and Hasties Computer Age Statistical Inference > > <https://hastie.su.domains/CASI_files/PDF/casi.pdf>, for a very broad > > overview of a wide range of computational statistics topics. > > > > Hastie, Tibshirani, and Friedman's Elements of Statistical Learning > > <https://hastie.su.domains/Papers/ESLII.pdf>, classic introduction to > > statistical machine learning. > > > > Gelman et al's Bayesian Data Analysis > > <http://www.stat.columbia.edu/~gelman/book/BDA3.pdf> for Bayesian > > modeling, but I haven't read any other books on this topic. > > > > I tend to just read the relevant documentation (pymc, pyro, pytorch, > > scikit-learn, scipy, statsmodels) to figure out how to do things in > Python. > > Hopefully someone else can chime in with more Python specific books. > > > > Best, > > Albert > > > > > > > > On Wed, Feb 15, 2023 at 10:31 AM Britta Smith <[email protected]> > > wrote: > > > >> Dear SciPy community, > >> What are your recommendations for textbooks concerning statistics and > >> data science? That hopefully go into depth about regression, and > hopefully > >> python. > >> Many thanks, > >> Britta > > --000000000000b8a94905f4c25b19 Content-Type: text/html; charset="UTF-8" Content-Transfer-Encoding: quoted-printable <div dir=3D"auto">I am a bit biased of course, but my online book could als= o meet your=C2=A0needs.<div dir=3D"auto"><br></div><div dir=3D"auto">Proces= s Improvement using Data. <a href=3D"https://learnche.org/pid/">https://lea= rnche.org/pid/</a></div><div dir=3D"auto"><br><div dir=3D"auto">Chapter 4 i= s about Regression, chapter 2 on fundamental stats, and chapter 5 on design= ed experiments (including a full online course on Coursera).</div><div dir= =3D"auto"><br></div><div dir=3D"auto">It's been a free, Creative Common= s licensed resource since 2010, and used by quite a number of industrial co= mpanies and universities daily.=C2=A0</div><div dir=3D"auto"><div dir=3D"au= to"><br></div><div dir=3D"auto">I'm working on converting the R code to= Python, so both are available side by side.=C2=A0 The repo is available on= GitHub if anyone is interested in helping speed that up ;)=C2=A0</div><div= dir=3D"auto"><a href=3D"https://github.com/kgdunn/pid-book">https://github= .com/kgdunn/pid-book</a></div><div dir=3D"auto"><div dir=3D"auto"><br></div= ><div dir=3D"auto">Kevin</div><div dir=3D"auto"><br><div class=3D"gmail_quo= te" dir=3D"auto"><blockquote class=3D"gmail_quote" style=3D"margin:0 0 0 .8= ex;border-left:1px #ccc solid;padding-left:1ex"> Date: Wed, 15 Feb 2023 12:42:48 -0500<br> From: David Nicholson <<a href=3D"mailto:[email protected]" rel=3D"nor= eferrer noreferrer" target=3D"_blank">[email protected]</a>><br> Subject: [SciPy-User] Re: Textbook Recommendations<br> To: SciPy Users List <<a href=3D"mailto:[email protected]" rel=3D"no= referrer noreferrer" target=3D"_blank">[email protected]</a>>=C2=A0<= br> <br> fwiw, some books from the Executable Books gallery (<br> <a href=3D"https://executablebooks.org/en/latest/gallery/" rel=3D"noreferre= r noreferrer noreferrer" target=3D"_blank">https://executablebooks.org/en/l= atest/gallery/</a>)<br> <br> <a href=3D"https://gulinan.github.io/mat244e/" rel=3D"noreferrer noreferrer= noreferrer" target=3D"_blank">https://gulinan.github.io/mat244e/</a><br> <a href=3D"http://theoryandpractice.org/stats-ds-book/intro.html" rel=3D"no= referrer noreferrer noreferrer" target=3D"_blank">http://theoryandpractice.= org/stats-ds-book/intro.html</a><br> <br> See also this translating Danielle Navarro's Learning Stats with R to<b= r> Python:<br> <a href=3D"https://ethanweed.github.io/pythonbook/landingpage.html" rel=3D"= noreferrer noreferrer noreferrer" target=3D"_blank">https://ethanweed.githu= b.io/pythonbook/landingpage.html</a><br> <br> David Nicholson, Ph.D.<br> <a href=3D"https://nicholdav.info/" rel=3D"noreferrer noreferrer noreferrer= " target=3D"_blank">https://nicholdav.info/</a><br> <a href=3D"https://github.com/NickleDave" rel=3D"noreferrer noreferrer nore= ferrer" target=3D"_blank">https://github.com/NickleDave</a><br> <br> <br> On Wed, Feb 15, 2023 at 11:47 AM Albert Steppi <<a href=3D"mailto:albert= [email protected]" rel=3D"noreferrer noreferrer" target=3D"_blank">albert.s= [email protected]</a>><br> wrote:<br> <br> > Hi Britta,<br> ><br> > I haven't read anything Python specific, but I like the following = books:<br> ><br> > For basic introductory stats, Freedman, Pisani, and Purves<br> > <<a href=3D"https://wwnorton.com/books/Statistics/" rel=3D"noreferr= er noreferrer noreferrer" target=3D"_blank">https://wwnorton.com/books/Stat= istics/</a>><br> ><br> > As a follow up, Freedman's Statistical Models: Theory and Practice= <br> > <<a href=3D"https://www.cambridge.org/core/books/statistical-models= /68F8872C7788AF62BD6513F7071EE1BA#fndtn-information" rel=3D"noreferrer nore= ferrer noreferrer" target=3D"_blank">https://www.cambridge.org/core/books/s= tatistical-models/68F8872C7788AF62BD6513F7071EE1BA#fndtn-information</a>>= ;,<br> > teaches one to think critically about regression modeling and its<br> > limitations.<br> ><br> > Efron and Hasties Computer Age Statistical Inference<br> > <<a href=3D"https://hastie.su.domains/CASI_files/PDF/casi.pdf" rel= =3D"noreferrer noreferrer noreferrer" target=3D"_blank">https://hastie.su.d= omains/CASI_files/PDF/casi.pdf</a>>, for a very broad<br> > overview of a wide range of computational statistics topics.<br> ><br> > Hastie, Tibshirani, and Friedman's Elements of Statistical Learnin= g<br> > <<a href=3D"https://hastie.su.domains/Papers/ESLII.pdf" rel=3D"nore= ferrer noreferrer noreferrer" target=3D"_blank">https://hastie.su.domains/P= apers/ESLII.pdf</a>>, classic introduction to<br> > statistical machine learning.<br> ><br> > Gelman et al's Bayesian Data Analysis<br> > <<a href=3D"http://www.stat.columbia.edu/~gelman/book/BDA3.pdf" rel= =3D"noreferrer noreferrer noreferrer" target=3D"_blank">http://www.stat.col= umbia.edu/~gelman/book/BDA3.pdf</a>> for Bayesian<br> > modeling, but I haven't read any other books on this topic.<br> ><br> > I tend to just read the relevant documentation (pymc, pyro, pytorch,<b= r> > scikit-learn, scipy, statsmodels) to figure out how to do things in Py= thon.<br> > Hopefully someone else can chime in with more Python specific books.<b= r> ><br> > Best,<br> > Albert<br> ><br> ><br> ><br> > On Wed, Feb 15, 2023 at 10:31 AM Britta Smith <<a href=3D"mailto:br= [email protected]" rel=3D"noreferrer noreferrer" target=3D"_blank">bretan= [email protected]</a>><br> > wrote:<br> ><br> >> Dear SciPy community,<br> >> What are your recommendations for textbooks concerning statistics = and<br> >> data science? That hopefully go into depth about regression, and h= opefully<br> >> python.<br> >> Many thanks,<br> >> Britta<br><br> </blockquote></div></div></div></div></div></div> --000000000000b8a94905f4c25b19-- --===============0687874826537178394== Content-Type: text/plain; charset="us-ascii" MIME-Version: 1.0 Content-Transfer-Encoding: 7bit Content-Disposition: inline _______________________________________________ SciPy-User mailing list -- [email protected] To unsubscribe send an email to [email protected] https://mail.python.org/mailman3/lists/scipy-user.python.org/ Member address: [email protected] --===============0687874826537178394==--