January 2019
Beginner to intermediate
576 pages
14h 31m
Chinese
Content preview from 深度學習｜內行人的做法
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O’Reilly covers everything we've got, with content to help us build a world-class technology community, upgrade the capabilities and competencies of our teams, and improve overall team performance as well as their engagement.I wanted to learn C and C++, but it didn't click for me until I picked up an O'Reilly book. When I went on the O’Reilly platform, I was astonished to find all the books there, plus live events and sandboxes so you could play around with the technology.I’ve been on the O’Reilly platform for more than eight years. I use a couple of learning platforms, but I'm on O'Reilly more than anybody else. When you're there, you start learning. I'm never disappointed.I'm always learning. So when I got on to O'Reilly, I was like a kid in a candy store. There are playlists. There are answers. There's on-demand training. It's worth its weight in gold, in terms of what it allows me to do.
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第六章：深度網路的調整
b. 可判斷輸出層所要採用的型態
3. 設定好網路架構，以支援問題的解決：
a. 模型、架構與成本函數的選擇，全都很重要
b. 根據所選擇的架構，選擇一些隱藏層
c. 根據網路整體架構與特定層的意圖，選擇每一層所要採用的激活函數
4. 針對訓練資料進行以下工作：
a. 清理資料
b. 生成視覺化結果
c. 執行向量化與歸一化操作
d. 針對類別間的數量均衡性進行調整（如果有必要的話）
e. 把資料拆分成測試組、訓練組與驗證組
5. 運用調整過均衡性的資料子集合，發展出超參數調整策略：
a. 盡可能增加子集合資料的數量，並根據需要調整超參數
6. 如果最終的訓練組資料數量很龐大，使用 Spark 就可以更快訓練更多的資料（在適
當的情況下）。
這些步驟在具體調整細節方面仍然是很高階的概念，但是它在我們要建立任何深度網路
時，給了我們可依循的通用途徑。到了本章的最後，我們希望你能擁有一整套完善的基
本調整原則，以便能夠更接近當今資料科學領域的最新發展。現在我們就來深入了解深
度網路調整方面的具體情況，首先從我們的流程第一步開始：設法找出能與輸入資料相
匹配的網路架構。
輸入資料
—
找出相匹配的網路架構
如前一節所述，在深度網路設計程序中，一開始必須先思考的是，來源資料集代表的究
竟是什麼樣的東西。這裡有一些例子：
• 欄位型資料
• 圖片資料
輸入資料
—
找出相匹配的網路架構
|
261
• 聲音資料
• 影片資料
• 時間序列資料
對於欄位型或逗號分隔型（CSV）資料來說 ...
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I'm always learning. So when I got on to O'Reilly, I was like a kid in a candy store. There are playlists. There are answers. There's on-demand training. It's worth its weight in gold, in terms of what it allows me to do.