Python Machine Learning Case Studies: Five Case Studies for the Data Scientist

Danish Haroon

Python Machine Learning Case Studies: Five Case Studies for the Data Scientist

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商品描述

Embrace machine learning approaches and Python to enable automatic rendering of rich insights and solve business problems. The book uses a hands-on case study-based approach to crack real-world applications to which machine learning concepts can be applied. These smarter machines will enable your business processes to achieve efficiencies on minimal time and resources.

Python Machine Learning Case Studies takes you through the steps to improve business processes and determine the pivotal points that frame strategies. You’ll see machine learning techniques that you can use to support your products and services. Moreover you’ll learn the pros and cons of each of the machine learning concepts to help you decide which one best suits your needs.

By taking a step-by-step approach to coding in Python you’ll be able to understand
the rationale behind model selection and decisions within the machine learning process. The book is equipped with practical examples along with code snippets to ensure that you understand the data science approach to solving real-world problems.

What You Will Learn
  • Gain insights into machine learning concepts 
  • Work on real-world applications of machine learning
  • Learn concepts of model selection and optimization
  • Get a hands-on overview of Python from a machine learning point of view

Who This Book Is For

Data scientists, data analysts, artificial intelligence engineers, big data enthusiasts, computer scientists, computer sciences students, and capital market analysts.


商品描述(中文翻譯)

採用機器學習方法和Python，實現自動生成豐富洞察力並解決業務問題。本書以實際案例為基礎，採用實踐性的方法來解決機器學習概念可應用於的現實應用。這些智能機器將使您的業務流程在最少的時間和資源下實現效率。

《Python機器學習案例研究》將引導您進一步改善業務流程，確定制定策略的關鍵點。您將學習到可用於支持產品和服務的機器學習技術。此外，您還將了解每個機器學習概念的優缺點，以幫助您決定哪個最適合您的需求。

通過逐步編寫Python代碼的方法，您將能夠理解模型選擇和機器學習過程中的決策原理。本書配有實際示例和代碼片段，以確保您理解數據科學方法解決現實問題的過程。

您將學到什麼：
- 獲取機器學習概念的洞察力
- 應用機器學習於實際應用
- 學習模型選擇和優化的概念
- 從機器學習的角度進行實踐性的Python概述

本書適合對象：
- 數據科學家、數據分析師、人工智能工程師、大數據愛好者、計算機科學家、計算機科學學生和資本市場分析師。

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