Khoa Công Nghệ Thông Tin
Handbook of big data analytics : 1st ed.
Addressing a broad range of big data analytics in cross-disciplinary applications, this essential handbook focuses on the statistical prospects offered by recent developments in this field. To do so, it covers statistical methods for high-dimensional problems, algorithmic designs, computation ...
- Vị trí lưu trữ: 03 Quang Trung
- Tổng sách: 1
- Đang rỗi: 1
You’ll start with the fundamentals of Python 3 programming language, machine learning history, evolution, and the system development frameworks. Key data mining/analysis concepts, such as exploratory analysis, feature dimension reduction, regressions, time series forecasting and their efficient ...
- Vị trí lưu trữ: 03 Quang Trung
- Tổng sách: 1
- Đang rỗi: 1
The book introduces machine learning and XGBoost in scikit-learn before building up to the theory behind gradient boosting. You'll cover decision trees and analyze bagging in the machine learning context, learning hyperparameters that extend to XGBoost along the way. You'll build gradient boosting ...
- Vị trí lưu trữ: 03 Quang Trung
- Tổng sách: 1
- Đang rỗi: 1
Complete guide to open source big data stack : 1st ed.
This book describes the creation of an actual generic open source big data stack, which is an integrated stack of big data components--each of which serves a specific function like storage, resource management, or queueing. Each component has a big data heritage and community to support it. It can ...
- Vị trí lưu trữ: 03 Quang Trung
- Tổng sách: 1
- Đang rỗi: 1
This book is a collection of chapters written by experts on various aspects of big data. The book aims to explain what big data is and how it is stored and used. The book starts from the fundamentals and builds up from there. It is intended to serve as a review of the state-of-the-practice in the ...
- Vị trí lưu trữ: 03 Quang Trung
- Tổng sách: 1
- Đang rỗi: 1