- 對 AI 概念的基本瞭解
- 熟悉 Google 雲平臺（推薦但不是必需的）
觀眾
- 非開發人員
- Business 專業人士
- 科技愛好者
定製聊天機器人是人工智慧驅動的對話代理，專為滿足用戶或企業的特定需求或要求而量身定製。這些聊天機器人可以經過訓練，以理解和回應查詢、執行任務以及在特定域或上下文中提供資訊。Google AutoML （Auto Machine Learning） 是 Google Cloud Platform 提供的一套機器學習產品和服務，使用戶能夠構建自定義機器學習模型，而無需在機器學習或編碼方面擁有廣泛的專業知識。AutoML 提供使用者友好的介面和強大的功能，使其易於訪問並吸引具有不同技術專長水平的使用者。
這種由講師指導的現場培訓（在線或現場）面向具有不同專業水平的參與者，他們希望利用 Google 的 AutoML 平臺為各種應用程式構建定製的聊天機器人。
在培訓結束時，參與者將能夠：
- 瞭解聊天機器人開發的基礎知識。
- 流覽 Google 雲平臺並訪問 AutoML。
- 為訓練聊天機器人模型準備數據。
- 使用 AutoML 訓練和評估自定義聊天機器人模型。
- 將聊天機器人部署並整合到各種平台和管道中。
- 隨時間推移監控和優化聊天機器人性能。
課程形式
- 互動講座和討論。
- 大量的練習和練習。
- 在現場實驗室環境中動手實施。
課程自定義選項
- 如需申請本課程的定製培訓，請聯繫我們進行安排。
聊天機器人開發簡介
- 聊天機器人及其應用概述
- 用於聊天機器人開發的 Google AutoML 簡介
- 瞭解聊天機器人的元件
Google Cloud Platform 和 AutoML 入門
- 設置 Google Cloud Platform 帳戶
- 導航 Google 雲控制台
- Accessing Google AutoML 並瞭解其特徵
聊天機器人培訓的數據準備
- 收集和預處理訓練數據
- 為聊天機器人意圖和實體標記數據
- 探索 Google Cloud Platform 中的數據可視化工具
使用 AutoML 訓練自定義聊天機器人模型
- 為聊天機器人開發創建一個新的 AutoML 專案
- 將訓練資料上傳和匯入AutoML
- 配置訓練設置和參數
評估和反覆運算聊天機器人模型
- 解釋聊天機器人性能的評估指標
- 根據評估結果反覆運算模型改進
- 微調聊天機器人模型以獲得更好的準確性和性能
聊天機器人的部署和集成
- 將聊天機器人部署到不同的平台和管道
- 將聊天機器人與網站、消息傳遞應用程式和其他介面集成
- 在真實場景中測試聊天機器人交互和用戶體驗
監控和優化聊天機器人性能
- 為已部署的聊天機器人設置監控和日誌記錄
- 分析使用數據和用戶反饋以提高聊天機器人性能
- 實施持續優化策略，實現長期成功
摘要和後續步驟
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