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: 7/25 Quang Trung
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Microbiology : Laboratory theory & application
Features include the following: Theory and Application provide students with the general principles and everyday purpose of the labs; "In This Exercise" clearly explains what students can expect as they work through the Lab Procedures; Biochemical Reactions for the Organism and Indicator Reactions...
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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...
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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...
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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: 7/25 Quang Trung
- Tổng sách: 1
- Đang rỗi: 1