Advanced Data Analytics Using Python: With Machine Learning, Deep Learning and NLP Examples

Sayan Mukhopadhyay

Advanced Data Analytics Using Python: With Machine Learning, Deep Learning and NLP Examples

買這商品的人也買了...

相關主題

商品描述

Gain a broad foundation of advanced data analytics concepts and discover the recent revolution in databases such as Neo4j, Elasticsearch, and MongoDB. This book discusses how to implement ETL techniques including topical crawling, which is applied in domains such as high-frequency algorithmic trading and goal-oriented dialog systems. You’ll also see examples of machine learning concepts such as semi-supervised learning, deep learning, and NLP. Advanced Data Analytics Using Python also covers important traditional data analysis techniques such as time series and principal component analysis. 
 
After reading this book you will have experience of every technical aspect of an analytics project. You’ll get to know the concepts using Python code, giving you samples to use in your own projects.
 
What You Will Learn
  • Work with data analysis techniques such as classification, clustering, regression, and forecasting
  • Handle structured and unstructured data, ETL techniques, and different kinds of databases such as Neo4j, Elasticsearch, MongoDB, and MySQL
  • Examine the different big data frameworks, including Hadoop and Spark
  • Discover advanced machine learning concepts such as semi-supervised learning, deep learning, and NLP
 
Who This Book Is For
 
Data scientists and software developers interested in the field of data analytics.
 
 

商品描述(中文翻譯)

獲得廣泛的高級數據分析概念基礎，並了解最近在Neo4j、Elasticsearch和MongoDB等數據庫中的革命。本書討論了如何實施ETL技術，包括在高頻算法交易和目標導向對話系統等領域應用的主題爬行。您還將看到機器學習概念的示例，例如半監督學習、深度學習和NLP。《使用Python進行高級數據分析》還涵蓋了重要的傳統數據分析技術，如時間序列和主成分分析。

閱讀本書後，您將獲得分析項目的每個技術方面的經驗。您將使用Python代碼了解這些概念，並獲得在自己的項目中使用的示例。

您將學到什麼：

- 使用分類、聚類、回歸和預測等數據分析技術
- 處理結構化和非結構化數據、ETL技術以及不同類型的數據庫，如Neo4j、Elasticsearch、MongoDB和MySQL
- 研究不同的大數據框架，包括Hadoop和Spark
- 探索半監督學習、深度學習和NLP等高級機器學習概念

本書適合對數據分析領域感興趣的數據科學家和軟件開發人員。

類似商品