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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

4,096 个评分
465 条评论


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...


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.

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 :)


326 - Launching into Machine Learning 的 350 个评论(共 467 个)

创建者 Matthew B

Jun 17, 2019

wish they teach you more of the programming side of things and knowing exactly what and why to upload different libraries and or show us how to build these in the labs. Not the first ML course, I've taken but some new people may be a bit confused on the python / setting up / sql even if they have a general knowledge to python and sql.

创建者 Evren G

Oct 11, 2018

Excellent course content. Would be 5 stars if the labs forced you to think about how you could apply your theoretical learnings. Unfortunately, labs already have all the code populated, so you just end up running things with the illusion that you have understood everything. Give us labs that require us to solve a problem!

创建者 aditya k

May 19, 2018

Very useful intro to data processing, specially the hashing mechanism to partition the datasets.

The last lab was confusing because the data might have some invalid value. in the jupyter notebook, the sin, and arcsin values were not getting computed (probably?) as I got warning from python .

创建者 Amir Y

Aug 31, 2018

I was initially considered that it was too mathematical. But you really don't need to understand the minute details and just get the concepts. good for someone like me that doesn't intend to code but be able to understand enough of challenges and the process for developing models.

创建者 Shivam K

Oct 1, 2019

Lesson Learnt: Best model might not be a good model in real world! Generalization is important!

The labs had issue of disconnection. My jupylab notebooks were frequently disconnecting from the server and I had to manually reconnect them to kernel.

创建者 R. K E P

Apr 19, 2020

Great introductory to Machine Learning, although the history part is a bit overwhelming for me because he is using a lot of jargon and there is a lack of visualization. But, the rest of the course is great, especially about the sampling.

创建者 Rohini M

Apr 20, 2019

Little challenging than the first part of the specialization but thoroughly enjoyed deep diving into understanding basic concepts of Machine Learning without being overwhelmed. Great for a person who does not have any previous knowledge.

创建者 Rakesh T

Feb 24, 2019

Will be good to dumb it down further. The last part is good, the first two parts can have better examples and find easier ways to explain the theoretical concepts for folks who have not heard these before.

创建者 Francois R

Apr 8, 2019

Tensorflow Playground is awesome to understand some of the theory of Deep Neural Nets !

Theory on creating/managing models was good too.

The labs with BigQuery were not that interesting too

创建者 Christian R

Aug 13, 2021

Interesting course, and the technical details during week 3 and 4 were highly appreicated. The labs could have been a bit better put together, but all round happy with this course!

创建者 Ankit R

Aug 17, 2019

I got a whole idea on how to work on data from scratch. Model selection, generalization, splitting of data and performance metric were few things I learned from this course.

创建者 Ashar M

Jul 14, 2018

Great presenter. High energy engaging. The material is more difficult and to develop intuition of why the sampling needs to result in constant RMSE didn't come across.

创建者 Phac L T

Jun 25, 2018

Overall it was great, and very instructive. However, the Short History of ML was a little bit confusing with too many unexplained words and too many details too early.

创建者 Seokchan Y

Apr 26, 2019

This course is more focused on technical side of using Google Cloud system.

It would be better if students could do mini-projects so that we get used to handling GCS.

创建者 Gautam S

Aug 19, 2018

Liked the way the datasplit using BigQuery is explained, but would appreciate if more references and links to explore BigQuery is provided at end of the video.

创建者 Sarthak k

May 10, 2020

Found only loophole in the description of why rmse not used for classification but i guess that was my lack of statistical skills . Anyways Thank You Google.

创建者 nuri k

Jun 25, 2020

Very informative and well-prepared course, the only downside is, other than quizzes, there is no user input involved. Highly recommended nonetheless.

创建者 Mario R

Jan 13, 2019

Nice course, kind of introductory but necessary for someone who has no knowledge about Machine Learning basics and most relevant algorithms so far.

创建者 Abhishek K

Aug 26, 2018

Very good course for beginners!

-1 star because I find labs to be less informational and practical and course to be more theoretical that practical!

创建者 Dimitry I

Oct 30, 2019

Good course. Teaches some basics of machine learning. Thank you to Google for putting it together, and to Coursera for making it available.

创建者 Ayman S

Jul 26, 2019

The instructor made several mistakes in reading the code like when he read the size of the file and interpreted as the number of records.

创建者 Abdullah K

Jun 14, 2019

some ideas discussed need further elaboration, and there should be a set of slides provided or notes that summarizes the key concepts.

创建者 zios s

Oct 3, 2019

High level of Machine learning algo and its implementation in cloud using Bigquery. simple but required in upcoming courses.

创建者 Afreen F

Nov 22, 2018

Theory is all good and important. Lab could have been made more challenging and not just mere marketing of Google products.

创建者 PLN R

Dec 9, 2018

It was quite an insightful and playful way to learn about how the world's biggest AI company deals with AI problems!