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学生对 Google 云端平台 提供的 Launching into Machine Learning 的评价和反馈

4.6
4,046 个评分
462 条评论

课程概述

Starting from a history of machine learning, we discuss why neural networks today perform so well in a variety of data science problems. We then discuss how to set up a supervised learning problem and find a good solution using gradient descent. This involves creating datasets that permit generalization; we talk about methods of doing so in a repeatable way that supports experimentation. Course Objectives: Identify why deep learning is currently popular Optimize and evaluate models using loss functions and performance metrics Mitigate common problems that arise in machine learning Create repeatable and scalable training, evaluation, and test datasets...

热门审阅

OD
May 30, 2020

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.

PT
Dec 1, 2018

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 :)

筛选依据:

451 - Launching into Machine Learning 的 464 个评论(共 464 个)

创建者 Francesco C

Jul 12, 2018

labs not really useful

创建者 Ligeng X

Nov 9, 2018

Barely learn anything

创建者 Nathaniel T

Jun 22, 2021

Although there are engaging lectures, they skip over all interesting technical detail to focus on philosophy (and of course lauding Google). Philosophy of data analysis is all good and well, but there is no technical instruction to go with it. Quizzes and labs stress technical details for which there is no instruction. Readings are a hodge-podge of unlabelled links with no prioritization or curation.

Labs take 15 mintues to start up, and then have 1-2 hour timeouts, at the end of which you lose all work you have done. There is little to no instruction in the labs: the only way to do them is either already understand what their topics (making them pointeless) or to quickly google up answers to technical questions, and blindly run functions (which is also pointless).

I have no idea how this course sequence was ever rated as an interesting one for qualification.

创建者 Yaron K

Jul 14, 2018

It's unclear for who this course is meant. It mixes basics like train-validate-test with lectures that use machine learning terms that only have meaning to someone who has already knows ML terminology. If you're looking for a good introduction to ML - check out Andrew Ng's course.

创建者 David S

Aug 16, 2019

"Short History of ML" was good, if kind of light. The rest of this course is flaming garbage. Zero topic organization. Material is poorly explained. Labs are poorly detailed and in some cases don't work out of the box. Seriously, skip this course and take Andrew Ng's instead.

创建者 Mike W

Jun 22, 2019

The notebook based demos are unfortunately pretty useless as labs. All of these courses would be much improved with real labs that require the student to build the system.

创建者 Arman A

Apr 11, 2019

Pros: Tensorflow is an excellent framework for deep learning

Cons :

1- The way this material is designed is 10 X SHIT

2- Either teach properly or don't teach at all.

创建者 Praveen K M

Feb 17, 2019

I'm not able to access the video lectures even though I purchased and completed this course 6 months back

创建者 Diretnan D

Nov 5, 2018

Too much scary information provided at once combined with the mindbending sql queries and data parsing

创建者 Ehsan F

Nov 13, 2018

This is the most superficial course I have ever taken. I just waisted my time.

创建者 Chi S S

Sep 1, 2018

Did not learn much! Poorly instructed courses.

创建者 Karim E

Aug 8, 2018

not well structured and lack handouts

创建者 sasidhar m

Jul 16, 2018

No hands on learning.

创建者 Avula A

Nov 3, 2020

i cant un enroll