April 2020
Intermediate to advanced
816 pages
18h 32m
Chinese
Content preview from 精通機器學習
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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.
323
第十一章
訓練深度神經網路
第
10
章介紹了人工神經網路
，
並且訓練了我們的第一個深度神經網路
。
但是它們都是淺
網路
，
只有幾個隱藏層而已
。
如果你需要處理複雜的問題
，
例如在高解析度的圖像中偵測
上百種物體該怎麼做
？
你要訓練深很多的
DNN，
或許用
10
層以上
，
每一層都有上百個神
經元
，
彼此間有數十萬個連結
。
訓練深度
DNN
並不輕鬆
，
以下是你可能遇到的問題
：
•
你可能會面臨麻煩的
梯度消失
（vanishing gradients）
問題
，
或相關的
梯度爆炸
（exploding gradients）
問題
，
它們是在訓練期間往回經歷
DNN
時
，
梯度越來越小
，
或
越來越大時發生的問題
。
這些問題都會讓較低的階層難以訓練
。
•
沒有足夠的資料可訓練大型的網路
，
或是為資料加上標籤的成本太高了
。
•
訓練速度可能超級緩慢
。
•
參數多達數百萬個的模型有很大的過擬訓練組風險
，
尤其是沒有足夠的訓練實例
，
或
它們的雜訊太多時
。
本章將討論這些問題並提出解決技術
。
我們會先探討梯度消失和爆炸問題
，
以及一些流行
的解決方案
。
接下來
，
我們要瞭解遷移學習以及無監督預先訓練
，
它們可協助你處理複雜
的問題
，
即使你只有一些有標籤的資料
。
接著我們要討論各種優化法
，
它們可以大幅提升
訓練大型模型的能力
。
最後
，
我們要探討一些流行的大型神經網路正則化技術
。
有了這些工具之後
，
你就可以訓練很深的網路了
。
歡迎光臨深度學習
！
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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.Julian F.
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.Addison B.
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.Amir M.
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.