学生对 Google 云端平台 提供的 Launching into Machine Learning 的评价和反馈
课程概述
热门审阅
Amazing course. For a beginner like me, it was a shot in the arm. Excellent presentation very lively and engaging. Hope to see the instructor soon in a another course. Thanks so much. I learned a lot.
This is an awesome module. It will open up so much inside story of ML process which is core of the topic with such a simplicity. It greatly increases my interest into this topic and this course :)
301 - Launching into Machine Learning 的 325 个评论（共 469 个）
创建者 엄윤식
•good
创建者 정태표
•good
创建者 김경훈
•Good
创建者 박성우
•good
创建者 강효진
•GOOD
创建者 kim m s
•good
创建者 김정민
•사랑해요
创建者 JeeinOh
•good
创建者 고상균
•good
创建者 unranker
•good
创建者 KimHJ
•good
创建者 dhokim
•nice
创建者 이동규
•good
创建者 Atichat P
•Good
创建者 Bruno E S B
•TOP
创建者 SOOFI O
•yes
创建者 Woojin J
•fun
创建者 吳金霖
•OK
创建者 지정수
•bu
创建者 ᄋᄋ
•..
创建者 K J
•11
创建者 Harshkumar
•NA
创建者 Matthias D
•T
创建者 Ravi P
•Very good course, but I did have some problems with how the instructors recommend reproducible splitting the Train, Validation and test datasets. By splitting on a date-hash you are not choosing a random sample. For example, in both the airplane and taxi example, If more winter dates were samples, we would expect more delays and longer taxi rides (and thus more expensive). Wouldn't it be better to split randomly, but reproducibly? In both R and Python SKlearn library you can 'set the seed' when splitting the data which seems like a much less biased and just as reproducible way to split the dataset. The other constructive criticism is to not give all the answers right away to encourage us students to actually write the SQL code (or at least part of it) ourselves.
创建者 Armen F
•This course provides a great synopsis of different machine learning models and their nuances. If you haven't seen machine learning before, you will probably need to go slowly and look up some of the concepts on your own. There are a lot of ML terms thrown around without any explanation, so be ready for that if you're new to this. The best part of the course was the Google TensorFlow Playground, where you can experiment with tuning neural networks to classify different types of datasets. The speakers in this course are all very good and the material is well organized. The reason for giving 4 stars is that the quizzes and lab exercises were much too easy, so anybody can get 100% for this course, which makes the grade (and passing score) meaningless.
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