Effective Amazon Machine Learning
暫譯: 有效的 Amazon 機器學習
Alexis Perrier
- 出版商: Packt Publishing
- 出版日期: 2017-04-28
- 定價: $1,650
- 售價: 6.0 折 $990
- 語言: 英文
- 頁數: 306
- 裝訂: Paperback
- ISBN: 1785883232
- ISBN-13: 9781785883231
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相關分類:
Machine Learning
立即出貨 (庫存 < 3)
商品描述
Key Features
- Create great machine learning models that combine the power of algorithms with interactive tools without worrying about the underlying complexity
- Learn the What's next? of machine learning―machine learning on the cloud―with this unique guide
- Create web services that allow you to perform affordable and fast machine learning on the cloud
Book Description
Predictive analytics is a complex domain requiring coding skills, an understanding of the mathematical concepts underpinning machine learning algorithms, and the ability to create compelling data visualizations. Following AWS simplifying Machine learning, this book will help you bring predictive analytics projects to fruition in three easy steps: data preparation, model tuning, and model selection.
This book will introduce you to the Amazon Machine Learning platform and will implement core data science concepts such as classification, regression, regularization, overfitting, model selection, and evaluation. Furthermore, you will learn to leverage the Amazon Web Service (AWS) ecosystem for extended access to data sources, implement realtime predictions, and run Amazon Machine Learning projects via the command line and the Python SDK.
Towards the end of the book, you will also learn how to apply these services to other problems, such as text mining, and to more complex datasets.
What you will learn
- Learn how to use the Amazon Machine Learning service from scratch for predictive analytics
- Gain hands-on experience of key Data Science concepts
- Solve classic regression and classification problems
- Run projects programmatically via the command line and the Python SDK
商品描述(中文翻譯)
主要特點
- 創建出色的機器學習模型,結合算法的力量與互動工具,而無需擔心底層的複雜性
- 透過這本獨特的指南,了解機器學習的下一步——雲端上的機器學習
- 創建網路服務,讓您能夠在雲端上進行經濟實惠且快速的機器學習
書籍描述
預測分析是一個複雜的領域,需要編碼技能、對機器學習算法背後數學概念的理解,以及創建引人注目的數據可視化的能力。這本書將幫助您在三個簡單步驟中實現預測分析項目:數據準備、模型調整和模型選擇,遵循 AWS 簡化機器學習的原則。
本書將介紹 Amazon Machine Learning 平台,並實現核心數據科學概念,如分類、回歸、正則化、過擬合、模型選擇和評估。此外,您將學會利用 Amazon Web Service (AWS) 生態系統來擴展數據來源的訪問,實現即時預測,並通過命令行和 Python SDK 運行 Amazon Machine Learning 項目。
在書的結尾,您還將學會如何將這些服務應用於其他問題,例如文本挖掘,以及更複雜的數據集。
您將學到什麼
- 學習如何從零開始使用 Amazon Machine Learning 服務進行預測分析
- 獲得關鍵數據科學概念的實踐經驗
- 解決經典的回歸和分類問題
- 通過命令行和 Python SDK 以程式化方式運行項目