Deep Learning Specialization (Coursera) Self-study record (C3W2)

Introduction

This is the content of Course 3, Week 2 (C3W2) of Deep Learning Specialization.

(C3W2L01) Carry Out Error Analysis

Contents

Image Dogs Great cat Blurry ... Comments
1 x
2 x
3 x x
...
% of total 8% 48% 61% ...

(C3W2L02) Cleaning up Incorrectly labeled data

Contents

--If the training set label is incorrect - DL algorithm are quite robust to random errors in the training set --systematic error has an effect (for example, if all white dogs are labeled "cats") --In case of Dev / Test set, perform error analysis. If the impact is large, correct it.

Image Dogs Great cat Blurry ... Incorrectly labeled Comments
1 x
2 x x
3 x x
...
% of total 8% 48% 61% ... 5%

(C3W2L03) Build First System Quickly, Then Iterate

Contents

comment

--Black after 5 minutes and 30 seconds

(C3W2L04) Training and testing on different distribution

Contents

--I want to develop an algorithm for classifying images in Mobile App ――But the collected data is 200k for the image (high pixel) from the web page and 10k for the mobile app data. What to do with train / dev / test data at this time? --Option 1; Add both to make 210k data and shuffle. - trainin set ; 205k - dev set ; 2.5k - test set ; 2.5k --Advantages; same distribution --Disadvantages; dev / test set is mostly web page data, not much mobile app data

(C3W2L05) Bias and Variance with mismatched data distribution

Contents

reference

-Deep Learning Specialization (Coursera) Self-study record (table of contents)

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