商品簡介
本書是一本機器學習實用指南，提供從基礎知識到進階技能的全面學習路徑。本書以淺顯 易懂的方式介紹了機器學習的基本概念和主要類型，並詳細介紹使用 Python 及常見的庫進行數 據處理和機器學習的實操。此外，介紹了數據預處理的詳細過程，最後通過若干典型案例加深 讀者對機器學習的理解。本書適合對機器學習感興趣的初學者，也可作為軟件開發人員、數據分析師、學術研究人員的參考書籍。
作者簡介
謝雪葵，畢業於北郵軟件學院計算機科學系軟件工程專業。在校期間，多次獲得專業一、二等獎學金，並成功帶領團隊進行了校園APP的研發工作。阿誠網絡的創始人，該公司專注於為企業提供大數據相關服務。主要業務包括為企業提供大數據技術支持和降低成本、提高效率的解決方案，同時也提供基於機器學習的預測模型和智能決策支持。在過去的多年裡，積累了豐富的企業級大數據項目實戰經驗，並負責大型銀行和互聯網公司的大數據項目開發和性能優化工作，其中包括使用機器學習技術進行風險評估、用戶行為分析和產品推薦等。
目次
目錄
機器學習入門············································································1
機器學習簡介 ···········································································1
1.1.1 什麼是機器學習································································1
1.1.2 機器學習的前景································································2
機器學習的主要類型 ··································································3
1.2.1 監督學習·········································································4
1.2.2 無監督學習······································································5
1.2.3 半監督學習······································································7
1.2.4 強化學習·········································································8
1.2.5 監督學習案例································································.10
選擇正確的算法·····································································.12
機器學習工具和環境·································································14
Python 介紹···········································································.14
2.1.1 Python 的安裝 ·······························································.14
2.1.2 Python 基礎語法 ····························································.19
2.1.3 Python 其他特性 ····························································.24
2.1.4 Python 簡單實戰案例(猜字遊戲) ····································.31
2.1.5 Python 高級實戰案例(網絡爬蟲) ····································.35
數據科學庫···········································································.38
2.2.1 NumPy ········································································.38
2.2.2 Pandas ·········································································.45
2.2.3 數據科學庫案例(電商網站) ··········································.54
機器學習庫···········································································.55
2.3.1 Scikit-Learn···································································.55
2.3.2 TensorFlow ···································································.60
2.3.3 Keras···········································································.64
2.3.4 機器學習庫案例(預測糖尿病) ·······································.67
數據預處理·············································································70
數據導入 ··············································································.70
數據清洗 ··············································································.71
特徵工程 ··············································································.73
3.3.1 特徵選擇······································································.73
3.3.2 特徵轉換······································································.75
3.3.3 特徵縮放······································································.77
數據分割 ··············································································.78
3.4.1 訓練集·········································································.78
3.4.2 測試集·········································································.79
3.4.3 驗證集·········································································.80
案例分析:銀行客戶數據·························································.80
機器學習模型的構建與評估························································84
監督學習實戰········································································.84
4.1.1 線性回歸······································································.84
4.1.2 邏輯回歸······································································.86
4.1.3 決策樹·········································································.88
4.1.4 隨機森林······································································.90
無監督學習實戰·····································································.91
4.2.1 K-means ·······································································.92
4.2.2 主成分分析···································································.93
深度學習實戰········································································.95
4.3.1 神經網絡······································································.95
4.3.2 卷積神經網絡··············
