文库 行业资料 AI

Machine Learning Yearning_Andrew Ng.pdf

AI PDF   23页   下载0   2026-01-26   浏览14   收藏0   点赞0   评分-   35312字   免费文档
温馨提示:当前文档最多只能预览 5 页,若文档总页数超出了 5 页,请下载原文档以浏览全部内容。
Machine Learning Yearning_Andrew Ng.pdf 第1页
Machine Learning Yearning_Andrew Ng.pdf 第2页
Machine Learning Yearning_Andrew Ng.pdf 第3页
剩余18页未读, 下载浏览全部
Page !1 Machine Learning Yearning-Draft V0.5 Andrew Ng Draft - Version 0.5 Draft - Version 0.5 Table of Contents (draft) Why Machine Learning Strategy 4 ........................................................................................... How to use this book to help your team 6 ................................................................................ Prerequisites and Notation 7 .................................................................................................... Scale drives machine learning progress 8 ................................................................................ Your development and test sets 11 ............................................................................................ Your dev and test sets should come from the same distribution 13 ........................................ How large do the dev/test sets need to be? 15 .......................................................................... Establish a single-number evaluation metric for your team to optimize 16 ........................... Optimizing and satisficing metrics 18 ..................................................................................... Having a dev set and metric speeds up iterations 20 ............................................................... When to change dev/test sets and metrics 21 .......................................................................... Takeaways: Setting up development and test sets 23 .............................................................. Build your first system quickly, then iterate 25 ........................................................................ Error analysis: Look at dev set examples to evaluate ideas 26 ................................................ Evaluate multiple ideas in parallel during error analysis 28 ................................................... If you have a large dev set, split it into two subsets, only one of which you look at 30 ........... H
Machine Learning Yearning_Andrew Ng.pdf