data-science-books
My data science reading list
Python Books
Python for Data Analysis: Data Wrangling with Pandas, NumPy, and IPython -- Wes McKinney, ISBN 978-1491957660
The leading book on Pandas, written by the developer of Pandas.
Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow -- Aurélien Géron, ISBN 978-1492032649
This book assumes that you know close to nothing about Machine Learning. Its goal is to give you the concepts, tools, and intuition you need to implement programs capable of learning from data. We will cover a large number of techniques, from the simplest and most commonly used (such as linear regression) to some of the Deep Learning techniques that regularly win competitions.
R Books
An Introduction to Statistical Learning: with Applications in R -- Gareth James, Daniela Witten, Trevor Hastie and Robert Tibshirani, ISBN 978-1461471370
Freely available at http://faculty.marshall.usc.edu/gareth-james/ISL/
An Introduction to Statistical Learning provides an accessible overview of the field of statistical learning, an essential toolset for making sense of the vast and complex data sets that have emerged in fields ranging from biology to finance to marketing to astrophysics in the past twenty years. This book presents some of the most important modeling and prediction techniques, along with relevant applications.
OSSU alternative for How To Code
Berkeley CS61A
Did anyone take a look at these courses from MIT? https://www.edx.org/course/software-construction-java-mitx-6-005-1x https://www.edx.org/course/advanced-software-construction-java-mitx-6-005-2x Both are archived but the course content readings/videos are still available. I suppose these readings can be used as supplementary resources while or after working on software construction series from ubc. What version of Java do they use? 8 Are there any alternatives to the UBC courses? cool, at least they're using a modern version of Java The book How to Design Programs can replace the How to Code courses The book is more comprehensive and I think It will take more time than the courses to finish. If you're going to be doing the book, do SICP not HTDP SICP is superior Teachyourselfcs.com SICP assumes more math knowledge though. If you already know Calculus, sure go with SICP. HtDP is for actual complete noobs and has no prerequisites
Tell me about 61A. Can you start it anytime or does it follow a real semester class? What approximate classes of OSSU does it replace? Thanks! Replaces SICP or HtDP/HtC (How to Code). You would want to do either 61AS which is self paced or self-pace yourself through an earlier run of 61A. Will give links later 61AS: https://berkeley-cs61as.github.io/textbook.html 61A with John DeNero: https://inst.eecs.berkeley.edu/~cs61a/sp18/ (Spring 2018 since Fall 2019 is ongoing) 61A with Brian Harvey: https://inst.eecs.berkeley.edu/~cs61a/sp11/ https://archive.org/details/ucberkeley-webcast-PL3E89002AA9B9879E?sort=titleSorter Put links to both teachers for 61A because TeachYourselfCS recommends the Harvey lectures. That's probably just because that was before they switched it to Python though 61AS actually looks like a great fit for replacing everything before Software Construction, but OSSU seems to really like stuff that grades you rather than having you rely on yourself so 🤷
Math resources
Linear Algebra and Differential Equations notes from Berkeley course https://math.berkeley.edu/~giventh/papers/ode.pdf
Learn Differential Equations: Up Close with Gilbert Strang and Cleve Moler -- MIT OCW course https://ocw.mit.edu/resources/res-18-009-learn-differential-equations-up-close-with-gilbert-strang-and-cleve-moler-fall-2015/