- Main
- Mathematics
- Probability and Statistics for Data...
Probability and Statistics for Data Science: Math + R + Data
Norman S. MatloffProbability and Statistics for Data Science: Math + R + Data covers "math stat"—distributions, expected value, estimation etc.—but takes the phrase "Data Science" in the title quite seriously:
* Real datasets are used extensively.
* All data analysis is supported by R coding.
* Includes many Data Science applications, such as PCA, mixture distributions, random graph models, Hidden Markov models, linear and logistic regression, and neural networks.
* Leads the student to think critically about the "how" and "why" of statistics, and to "see the big picture."
* Not "theorem/proof"-oriented, but concepts and models are stated in a mathematically precise manner.
Prerequisites are calculus, some matrix algebra, and some experience in programming.
Norman Matloff is a professor of computer science at the University of California, Davis, and was formerly a statistics professor there. He is on the editorial boards of the Journal of Statistical Software and The R Journal. His book Statistical Regression and Classification: From Linear Models to Machine Learning was the recipient of the Ziegel Award for the best book reviewed in Technometrics in 2017. He is a recipient of his university's Distinguished Teaching Award.
Dosya 1-5 dakika içinde Telegram hesabınıza teslim edilecektir.
Not: Hesabınızı Z-Library Telegram botuna bağladığınızdan emin olun.
Dosya 1-5 dakika içinde Kindle cihazınıza teslim edilecektir.
Not: Kindle'a gönderdiğiniz her kitabı doğrulamanız gerekir. Amazon Kindle Support'tan gelen bir onay e-postası için e-posta gelen kutunuzu kontrol edin.
- E-okuyuculara gönderin
- Arttırılmış indirme limiti
- Dosyaları dönüştürün
- Diğer arama sonuçları
- Diğer avantajları