Hands-On Data Science and Machine Learning with Python
暫譯: 實戰數據科學與機器學習:使用 Python

Frank Kane

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商品描述

Key Features

  • Take your first steps in the world of data science by understanding the tools and techniques of data analysis
  • Train efficient Machine Learning models in Python using the supervised and unsupervised learning methods
  • Learn how to use Apache Spark for processing Big Data efficiently

Book Description

The job of a data scientist is one of the most lucrative jobs out there today - it involves analyzing large amounts of data, and gathering actionable business insights from it using a variety of tools.

This book will help you take your first steps in the world of data science, and empower you to conduct data analysis and perform efficient machine learning using Python. Gain value from your data using the various data mining and data analysis techniques in Python, and develop efficient predictive models to predict future results. You will also learn how to perform large-scale machine learning on Big Data using Apache Spark. It covers preparing your data for analysis, training machine learning models, and visualizing the final data analysis.

You don't have to be an expert coder in Python to get the most out of this book - just a basic programming knowledge of Python is sufficient.

What you will learn

  • Learn how to clean your data and ready it for analysis Implement the popular clustering and regression methods in Python
  • Train efficient machine learning models using Decision Trees and Random Forests
  • Visualize the results of your analysis using Python's Matplotlib library
  • Use Apache Spark's MLLib package to perform machine learning on large datasets

商品描述(中文翻譯)

**主要特點**

- 透過了解數據分析的工具和技術,邁出數據科學世界的第一步
- 使用監督式和非監督式學習方法,在 Python 中訓練高效的機器學習模型
- 學習如何使用 Apache Spark 高效處理大數據

**書籍描述**

數據科學家的工作是當今最具利潤的職業之一——它涉及分析大量數據,並使用各種工具從中獲取可行的商業洞察。

本書將幫助您在數據科學的世界中邁出第一步,並使您能夠使用 Python 進行數據分析和高效的機器學習。利用 Python 中的各種數據挖掘和數據分析技術,從您的數據中獲取價值,並開發高效的預測模型以預測未來結果。您還將學習如何使用 Apache Spark 在大數據上執行大規模機器學習。本書涵蓋了為分析準備數據、訓練機器學習模型以及可視化最終數據分析的過程。

您不必是 Python 的專家編碼者即可充分利用本書——只需具備基本的 Python 編程知識即可。

**您將學到的內容**

- 學習如何清理數據並為分析做好準備,實現 Python 中流行的聚類和回歸方法
- 使用決策樹和隨機森林訓練高效的機器學習模型
- 使用 Python 的 Matplotlib 庫可視化分析結果
- 使用 Apache Spark 的 MLLib 套件在大型數據集上執行機器學習