- 對人工智慧和機器學習有基本的瞭解
- 熟練使用 Python 程式設計
- 熟悉數據處理和預處理
觀眾
- 人工智慧研究人員
- 數據科學家
- 機器學習工程師
多模態人工智慧是一個創新領域，它結合了來自各種感官輸入的資訊，以創建以更像人類的方式理解世界並與之互動的系統。
這種由講師指導的現場培訓（在線或現場）面向希望創建能夠處理和解釋多模態數據的智慧系統的中級人工智慧研究人員、數據科學家和機器學習工程師。
在培訓結束時，參與者將能夠：
- 瞭解多模態 AI 及其應用的原理。
- 實施數據融合技術以組合不同類型的數據。
- 構建和訓練可以處理視覺、文本和聽覺資訊的模型。
- 評估多模態 AI 系統的性能。
- 解決與多模態數據相關的道德和隱私問題。
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。
多模態 AI 簡介
- 瞭解多模態數據
- 關鍵概念和定義
- 多模態學習的歷史和演變
多模態數據處理
- 數據收集和預處理
- 從不同模式中提取特徵
- 數據融合技術
多模態表示學習
- 學習聯合表示
- 跨模態嵌入
- 跨模式的遷移學習
多模態對齊和翻譯
- 對齊來自多種模態的數據
- 跨模態檢索系統
- 模態之間的翻譯（例如，文字到圖像、圖像到文字）
多模態推理與推理
- 使用多模態數據進行邏輯和推理
- 多模態 AI 中的推理技術
- 在問答和決策中的應用
多模態 AI 中的生成模型
- 用於多模態資料產生對抗網路 （GAN）
- 用於跨模態產生的變分自動編碼器 （VAE）
- 生成式多模態人工智慧的創造性應用
多模態融合技術
- 早期、晚期和混合融合方法
- 多模態融合中的注意力機制
- 融合，實現強大的感知和交互
多模態AI的應用
- 多模態人機交互
- 自動駕駛汽車中的人工智慧
- 醫療保健應用（例如，醫學成像和診斷）
倫理考慮與挑戰
- 多式聯運系統中的偏差和公平性
- 多模態數據的隱私問題
- 多模態人工智慧系統的道德設計和部署
多模態 AI 中的高級主題
- 多模態變壓器
- 多模態人工智慧中的自監督學習
- 多模態機器學習的未來
摘要和後續步驟
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