Statistical Learning with Math and R
Joe Suzuki
Informasi Umum
Kode
22.21.726
Klasifikasi
519.5 - Statistical mathematics, parametric and nonparametric methods
Jenis
Buku - Elektronik (E-Book)
Subjek
Statistical Mathematics
No. Rak
10b
Dilihat
4 kali
Informasi Lainnya
Abstraksi
The most crucial ability for machine learning and data science is mathematical logic for grasping their essence rather than knowledge and experience. This textbook approaches the essence of machine learning and data science by considering math problems and building R programs. As the preliminary part, Chapter 1 provides a concise introduction to linear algebra, which will help novices read further to the following main chapters. Those succeeding chapters present essential topics in statistical learning: linear regression, classification, resampling, information criteria, regularization, nonlinear regression, decision trees, support vector machines, and unsupervised learning.
Each chapter mathematically formulates and solves machine learning problems and builds the programs. The body of a chapter is accompanied by proofs and programs in an appendix, with exercises at the end of the chapter. Because the book is carefully organized to provide the solutions to the exercises in each chapter, readers can solve the total of 100 exercises by simply following the contents of each chapter.
Koleksi & Sirkulasi
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Pengarang
| Nama | Joe Suzuki |
| Jenis | Perorangan |
| Penyunting | |
| Penerjemah |
Penerbit
| Nama | Springer |
| Kota | New York |
| Tahun | 2020 |
Sirkulasi
| Harga sewa | IDR 0,00 |
| Denda harian | IDR 0,00 |
| Jenis | Non-Sirkulasi |
