Model book rec tweaks
This commit is contained in:
parent
6b6c867c51
commit
e798dac411
14
model.Rmd
14
model.Rmd
|
@ -65,18 +65,20 @@ The modelling chapters are even more opinionated than the rest of the book. I ap
|
||||||
* *Statistical Modeling: A Fresh Approach* by Danny Kaplan,
|
* *Statistical Modeling: A Fresh Approach* by Danny Kaplan,
|
||||||
<http://www.mosaic-web.org/go/StatisticalModeling/>. This book provides
|
<http://www.mosaic-web.org/go/StatisticalModeling/>. This book provides
|
||||||
a gentle introduction to modelling, where you build your intuition,
|
a gentle introduction to modelling, where you build your intuition,
|
||||||
mathematical tools, and R skills in parallel.
|
mathematical tools, and R skills in parallel. The book replaces a traditional
|
||||||
|
"introduction to statistics" course, providing a curriculum that is up-to-date
|
||||||
|
and relevant to data science.
|
||||||
|
|
||||||
* *An Introduction to Statistical Learning* by Gareth James, Daniela Witten,
|
* *An Introduction to Statistical Learning* by Gareth James, Daniela Witten,
|
||||||
Trevor Hastie, and Robert Tibshirani, <http://www-bcf.usc.edu/~gareth/ISL/>
|
Trevor Hastie, and Robert Tibshirani, <http://www-bcf.usc.edu/~gareth/ISL/>
|
||||||
(available online for free). This book presents a family of modern modelling
|
(available online for free). This book presents a family of modern modelling
|
||||||
techniques collectively known as statistical learning.
|
techniques collectively known as statistical learning. For an even deeper
|
||||||
|
understanding of the math behind the models, read the classic
|
||||||
|
*Elements of Statistical Learning* by Trevor Hastie, Robert Tibshirani, and
|
||||||
|
Jerome Friedman, <http://statweb.stanford.edu/~tibs/ElemStatLearn/> (also
|
||||||
|
available online for free).
|
||||||
|
|
||||||
* *Applied Predictive Modeling* by Max Kuhn and Kjell Johnson,
|
* *Applied Predictive Modeling* by Max Kuhn and Kjell Johnson,
|
||||||
<http://appliedpredictivemodeling.com>. This book is a companion to the
|
<http://appliedpredictivemodeling.com>. This book is a companion to the
|
||||||
__caret__ package, and provides practical tools for dealing with real-life
|
__caret__ package, and provides practical tools for dealing with real-life
|
||||||
predictive modelling challenges.
|
predictive modelling challenges.
|
||||||
|
|
||||||
<!--
|
|
||||||
For much of the insirpiration of the visualisations of these models, and extensions to more complex families, you might like "MODEL VIS PAPER"
|
|
||||||
-->
|
|
||||||
|
|
Loading…
Reference in New Issue