April 2020
Intermediate to advanced
816 pages
18h 32m
Chinese
Overview
建立智慧系統的概念、工具與技術
“這是一本卓越的機器學習資源，有清楚、直觀的解說，以及大量實用技巧。” —François Chollet Keras作者，《Deep Learning with Python》作者
“這本書詳細介紹以神經網路解決問題的理論與做法；建議想要實際運用ML的人都要看這本書。” —Pete Warden TensorFlow行動主管
深度學習經歷了一系列的突破之後，已經大幅推動了整個機器學習領域，如今，即使你對這項技術一無所知，也可以使用簡單、高效的工具，製作可從資料中學習的程式。這本暢銷書新版本使用具體的案例、精簡的理論，以及Python準生產框架，協助你直觀地認識智慧系統的概念與建構工具。
你將學到可快速上手的技術，只要具備程式編寫經驗，就可以藉由各章的習題來學習。你可以在GitHub取得本書的所有程式碼，這些程式已經更新為TensorFlow 2，以及最新版的Scikit-Learn。
- 使用Scikit-Learn與pandas，透過端對端專案建立機器學習基礎
- 用TensorFlow 2建構與訓練許多神經網路架構，以進行分類及回歸
- 探索物體偵測、語義分割、專注機制、語言模型、GAN等
- 探索TensorFlow 2的官方高階API—Keras API
- 使用TensorFlow的Data API、分散式策略API、TF Transform及TF-Serving將TensorFlow模型生產化
- 在Google Cloud AI Platform或行動裝置上部署
- 瞭解降維、分群及異常檢測等非監督學習技術
- 用強化學習來建立自主學習代理程式(agent)，包括使用TF-Agents程式庫
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