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.
機器學習的主要挑戰
|
23
我們已經討論許多領域了
，
你已經瞭解機器學習真正的含義
、
為什麼它很有用
、ML
系統
常見的種類
，
以及典型的專案工作流程長怎樣
。
接下來要看看在學習過程中可能出錯
，
並
阻止你做出準確預測的地方有哪些
。
機器學習的主要挑戰
簡單來說
，
因為你的主要工作是選擇學習演算法
，
並且用一些資料來訓練它
，
所以可能出
錯的東西就是
「
不良的演算法
」
與
「
不良的資料
」。
我們從不良資料談起
。
訓練資料不足
要讓一位蹣跚學步的小孩知道什麼是蘋果
，
你只要指著一個蘋果說
「
蘋果
」（
可能要重複
幾次
），
就可以讓孩子認出各種顏色與形狀的蘋果了
。
小孩真的很聰明
。
機器學習還不到這種程度
，
大多數的機器學習演算法都需要大量的資料才能正確運作
。
就算是非常簡單的問題
，
你通常也要用上千個樣本
，
當問題很複雜時
，
例如圖像或語音辨
識
，
你可能需要數百萬個樣本
（
除非你可以重複使用既有的模型的某些部分
）。
資料的影響力出人意料
Microsoft
的研究者
Michele Banko
和
Eric Brill
在一篇
2001
發表的著名論文
（https://homl.info/6）
中展示
，
當彼此差異極大的機器學習演算法
（
包括相當簡
單的演算法
）
獲得足夠的資料時
，
它們處理自然語言歧義消除
（natural language
disambiguation）
8
這種複雜問題的表現幾乎一模一樣
（
見圖
1-20）。
8
例如
，
可以根據上下文知道究竟該寫出
“to”、“two”
或
“too”。
24
|
第一章：機器學習領域
圖
1-20
資料
vs.
演算法的重要性
9
作者說
「
根據這些結果 ...
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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.