Statistical Learning

Academy
edX
Kurzbeschreibung
Learn some of the main tools used in statistical modeling and data science. We cover both traditional as well as exciting new methods, and h... mehr...

Learn some of the main tools used in statistical modeling and data science. We cover both traditional as well as exciting new methods, and how to use them in R.

weniger
Kursarten
E-Learning

Dieser Kurs ist neu hier. 0 User folgen diesem Kurs und erhalten Bescheid, wenn es Neues gibt - Kurs jetzt folgen.

Du hast den Kurs besucht? Kurs jetzt bewerten.

Hier kannst du der Eggheads Community deine Fragen zu diesem Kurs stellen. Auch Kursleiter können mitdiskutieren.


Frage stellen

Du must angemeldet sein um zu antworten

Kursinhalt
This is an introductory-level course in supervised learning, with a focus on regression and classification methods. The syllabus includes: linear and polynomial regression, logistic regression and linear discriminant analysis; cross-validation and the bootstrap, model selection and regularization methods (ridge and lasso); nonlinear models, splines and generalized additive models; tree-based methods, random forests and boosting; support-vector machines. Some unsupervised learning methods are discussed: principal components and clustering (k-means and hierarchical). This is not a math-heavy class, so we try and describe the methods without heavy reliance on formulas and complex mathematics. We focus on what we consider to be the important elements of modern data analysis. Computing is done in R. There are lectures devoted to R, giving tutorials from the ground up, and progressing with more detailed sessions that implement the techniques in each chapter. The lectures cover all the material in An Introduction to Statistical Learning, with Applications in R by James, Witten, Hastie and Tibshirani (Springer, 2013). The pdf for this book is available for free on the book website.
Kurssprache
Englisch
Kursgebühr
USD 50