- 了解機器學習概念
- Python 程式設計經驗
觀眾
- 數據科學家
- 軟體工程師
AdaBoost 是一種與其他機器學習模型一起使用以實現最佳性能的演算法。它使用集成學習技術，將較弱的模型組合在一起，以形成更準確的預測。
這種講師指導的現場培訓（在線或現場）面向希望使用 AdaBoost 構建機器學習提升演算法的數據科學家和軟體工程師 Python。
在本次培訓結束時，參與者將能夠：
- 設置必要的開發環境，開始使用 AdaBoost 構建機器學習模型。
- 瞭解集成學習方法以及如何實現自適應提升。
- 在 Python 中瞭解如何構建 AdaBoost 模型來提升機器學習演算法。
- 使用超參數優化來提高 AdaBoost 模型的準確性和性能。
課程形式
- 互動講座和討論。
- 大量的練習和練習。
- 在即時實驗室環境中動手實施。
課程自定義選項
- 要申請本課程的定製培訓，請聯繫我們進行安排。
介紹
- AdaBoost 特性和優勢概述
- 瞭解集成學習方法
開始
- 設置庫（Numpy、Pandas、Matplotlib 等）
- 導入或載入數據集
使用 Python 構建 AdaBoost 模型
- 準備用於訓練的數據集
- 使用 AdaBoostClassifier 創建實例
- 訓練數據模型
- 計算和評估測試數據
使用超參數
- 探索 AdaBoost 中的超參數
- 設置值並訓練模型
- 修改超參數以提高性能
最佳實踐和故障排除提示
總結和後續步驟
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