- Scala for Machine Learning(Second Edition)
- Patrick R. Nicolas
- 145字
- 2021-07-08 10:43:01
What you need for this book
A decent command of the Scala programming language is a prerequisite. Reading through a mathematical formulation, conveniently defied in an information box, is optional. However, some basic knowledge of mathematics and statistics might be helpful to understand the inner workings of some algorithms.
The book uses the following libraries:
- Scala 2.11.8 or higher
- Java 1.8.0_25
- SBT 0.13 or higher
- JFreeChart 1.0.17
- Apache Commons Math library 3.5 (Chapter 3, Data Pre-processing, Chapter 4, Unsupervised Learning, and Chapter 9, Regression and Regularization)
- Indian Institute of Technology Bombay CRF 0.2 (Chapter 7, Sequential Data Models)
- LIBSVM 0.1.6 (Chapter 8, Kernel Models and Support Vector Machines)
- Akka 2.3.8 or higher (or Typesafe activator 1.2.10 or higher) (Chapter 16, Parallelism in Scala and Akka)
- Apache Spark 2.1.0 or higher (Chapter 17, Apache Spark MLlib)
Tip
Understanding the mathematical formulation of a model is optional.
推薦閱讀
- Objective-C Memory Management Essentials
- SQL學習指南(第3版)
- Java FX應用開發教程
- 老“碼”識途
- Python高效開發實戰:Django、Tornado、Flask、Twisted(第3版)
- Securing WebLogic Server 12c
- 名師講壇:Java微服務架構實戰(SpringBoot+SpringCloud+Docker+RabbitMQ)
- C++ 從入門到項目實踐(超值版)
- 區塊鏈技術與應用
- Getting Started with Eclipse Juno
- Learning Apache Karaf
- RESTful Java Web Services(Second Edition)
- Vue.js 2 Web Development Projects
- JavaScript程序設計(第2版)
- 并行編程方法與優化實踐