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.

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.

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.

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.

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

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

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!

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

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.

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

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

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

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

Detailed overview of Data Preparation for ML, however it just gives a walk through of a single example on Big Query

overall very useful to get into ML world.

But in the lab, couldn't run the re coded set as instructed.

Thank you!

Overall is a good course. I'll suggest to improve the algorithms description, also go slow in code deployed.

Nice reviews and explanations, could be improved a little by ensuring students to write code themselves.

Some of the lecture has only talking, would be better if it got included more slides/reading materials.

Great to get some theoretical background on machine learning as well as some practical experience

Along with the complete codes, should also have some hands-on exercises for students to work on.

Muy bien explicado, los quices relacionados con los temas vistos anteriormente y los Notebooks

Good lectures, but the labs are very directed which makes it hard to learn much from them.

Not very academically robust, but a nice quick intro to some of the real concepts of ML.

A teacher's presentation skill needs to be improved. His speaking sometimes is blur.

Pretty good overall, missed the point of the labs a bit until I watched the review.