Hands-On Predictive Analytics with Python: A practical guide to building high performance predictive analytics solutions with Python
暫譯: 實戰預測分析與Python:構建高效能預測分析解決方案的實用指南
Alvaro Fuentes
- 出版商: Packt Publishing
- 出版日期: 2018-12-28
- 售價: $2,010
- 貴賓價: 9.5 折 $1,910
- 語言: 英文
- 頁數: 374
- 裝訂: Paperback
- ISBN: 178913871X
- ISBN-13: 9781789138719
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相關分類:
Python、程式語言、Machine Learning
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相關翻譯:
Python 預測分析實戰 (簡中版)
海外代購書籍(需單獨結帳)
商品描述
Step-by-step guide to build high performing predictive applications
Key Features
- Master how to use Python and its data analytics ecosystem to implement end-to-end Predictive Analytics projects
- Explore advanced predictive modeling algorithms such as support vector machine, apriori, and neural networks
- Find the right balance between theory, intuition and practice to be a useful resource for practitioners
Book Description
Predictive Analytics involves meticulous usage of data, statistical algorithms and techniques of machine learning in establishing the future outcomes based on historical data.
This book provides practical coverage in understanding important concepts of predictive analytics, how to process massive data sets, building predictive models along with usage of cutting-edge python tools and packages. The book walks you step-by-step right from defining the problem statement, identifying relevant data, performing data treatment, synthesizing analytics model and optimizing them with effective Python codes. You will understand each and every phase of predictive analytics process with the help of successful demonstrated applications. You will work with predictive algorithms such as SVM, k-NN, Apriori algorithm, NLP process and neural networks. You will learn to code with various python libraries such as TensorFlow, NumPy, SciPy, pandas and build machine learning models, intuitive visualizations, performing complex calculations and achieving actionable predictive results.
With this book, you will be all set to build the predictive analytic application with practical examples and best practices using robust tools of python programming.
What you will learn
- Understand the main concepts and principles of Predictive Analytics and how to use them when building real-world predictive models.
- Properly use scikit-learn, the main Python library for Predictive Analytics and Machine Learning.
- Learn the types of Predictive Analytics problem and how to apply the main models and algorithms to solve real world problems.
- Build, evaluate, and interpret classification and regression models on real-world datasets.
- Prepare a dataset for modelling and extract information using Exploratory Data Analysis
- Explore how to implement a predictive model as a web application
Who This Book Is For
This book is for Python programmers who wants to learn predictive modeling and aspire to enter data science and machine learning areas. All you need is basic familiarity with linear algebra and statistical knowledge.
商品描述(中文翻譯)
**逐步指南:建立高效能的預測應用程式**
#### 主要特點
- 精通如何使用 Python 及其數據分析生態系統來實現端到端的預測分析專案
- 探索先進的預測建模演算法,如支持向量機(support vector machine)、Apriori 演算法和神經網絡
- 找到理論、直覺和實踐之間的正確平衡,成為實務工作者的有用資源
#### 書籍描述
預測分析涉及對數據、統計演算法和機器學習技術的精細使用,以根據歷史數據建立未來結果。
本書提供了實用的內容,幫助讀者理解預測分析的重要概念、如何處理大量數據集、建立預測模型以及使用尖端的 Python 工具和套件。本書逐步引導您從定義問題陳述、識別相關數據、執行數據處理、合成分析模型到使用有效的 Python 代碼進行優化。您將在成功示範的應用程式幫助下,理解預測分析過程的每一個階段。您將使用預測演算法,如 SVM、k-NN、Apriori 演算法、自然語言處理(NLP)過程和神經網絡。您將學會使用各種 Python 函式庫,如 TensorFlow、NumPy、SciPy、pandas,來建立機器學習模型、直觀的可視化、執行複雜計算並獲得可行的預測結果。
有了這本書,您將準備好使用 Python 程式設計的穩健工具,通過實際範例和最佳實踐來建立預測分析應用程式。
#### 您將學到什麼
- 理解預測分析的主要概念和原則,以及在建立現實世界的預測模型時如何使用它們。
- 正確使用 scikit-learn,這是預測分析和機器學習的主要 Python 函式庫。
- 學習預測分析問題的類型,以及如何應用主要模型和演算法來解決現實世界的問題。
- 在現實世界數據集上建立、評估和解釋分類和回歸模型。
- 準備數據集以進行建模,並使用探索性數據分析提取信息。
- 探索如何將預測模型實現為網頁應用程式。
#### 本書適合誰
本書適合希望學習預測建模並渴望進入數據科學和機器學習領域的 Python 程式設計師。您只需對線性代數和統計知識有基本的熟悉。