Python Machine Learning By Example

Key Features

• Learn the fundamentals of machine learning and build your own intelligent applications
• Master the art of building your own machine learning systems with this example-based practical guide
• Work with important classification and regression algorithms and other machine learning techniques

Book Description

Data science and machine learning are some of the top buzzwords in the technical world today. A resurging interest in machine learning is due to the same factors that have made data mining and Bayesian analysis more popular than ever. This book is your entry point to machine learning.

This book starts with an introduction to machine learning and the Python language and shows you how to complete the setup. Moving ahead, you will learn all the important concepts such as, exploratory data analysis, data preprocessing, feature extraction, data visualization and clustering, classification, regression and model performance evaluation. With the help of various projects included, you will find it intriguing to acquire the mechanics of several important machine learning algorithms - they are no more obscure as they thought. Also, you will be guided step by step to build your own models from scratch. Toward the end, you will gather a broad picture of the machine learning ecosystem and best practices of applying machine learning techniques.

Through this book, you will learn to tackle data-driven problems and implement your solutions with the powerful yet simple language, Python. Interesting and easy-to-follow examples, to name some, news topic classification, spam email detection, online ad click-through prediction, stock prices forecast, will keep you glued till you reach your goal.

What you will learn

• Exploit the power of Python to handle data extraction, manipulation, and exploration techniques
• Use Python to visualize data spread across multiple dimensions and extract useful features
• Dive deep into the world of analytics to predict situations correctly
• Implement machine learning classification and regression algorithms from scratch in Python
• Be amazed to see the algorithms in action
• Evaluate the performance of a machine learning model and optimize it
• Solve interesting real-world problems using machine learning and Python as the journey unfolds

主要特點

- 學習機器學習的基礎知識，並建立自己的智能應用程式
- 通過實例為基礎的實用指南，掌握構建自己的機器學習系統的技巧
- 使用重要的分類和回歸算法以及其他機器學習技術

書籍描述

數據科學和機器學習是當今技術世界中的熱門詞語。機器學習的重新興趣是由於數據挖掘和貝葉斯分析變得比以往更受歡迎的相同因素。本書是您進入機器學習的入口。

本書從機器學習和Python語言的介紹開始，並向您展示如何完成設置。隨著進一步的學習，您將學習到所有重要的概念，如探索性數據分析、數據預處理、特徵提取、數據可視化和聚類、分類、回歸和模型性能評估。通過包含的各種項目的幫助，您將發現學習幾個重要的機器學習算法的過程非常有趣 - 它們不再像以前那樣晦澀難懂。此外，您將逐步指導如何從頭開始構建自己的模型。最後，您將獲得機器學習生態系統的整體圖景和應用機器學習技術的最佳實踐。

通過本書，您將學習解決數據驅動問題並使用強大而簡單的Python語言實施解決方案。有趣且易於跟隨的示例，例如新聞主題分類、垃圾郵件檢測、在線廣告點擊預測、股票價格預測，將使您一直保持興趣，直到達到目標。

您將學到的內容

- 利用Python處理數據提取、操作和探索技術的能力
- 使用Python將數據可視化在多個維度上分佈並提取有用的特徵
- 深入研究分析領域，正確預測情況
- 在Python中從頭開始實現機器學習分類和回歸算法
- 看到算法在實際應用中的驚人效果
- 評估機器學習模型的性能並進行優化
- 在旅程展開的過程中，使用機器學習和Python解決有趣的現實問題