Feature Engineering
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| Rating | 4.0★ based on 126 ratings |
|---|---|
| Length | 4 weeks |
| Effort | 2 weeks of study, 5-7 hours per week |
| Starts | Jul 3 (43 weeks ago) |
| Cost | $49 |
| From | Google Cloud via Coursera |
| Instructor | Google Cloud Training |
| Download Videos | On all desktop and mobile devices |
| Language | English |
| Subjects | Data Science Programming IT & Networking |
| Tags | Data Science Machine Learning Cloud Computing Information Technology |
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What people are saying
feature engineering
With examples and explanation how your model can improve with feature engineering did the trick.
Learned lots of stuff on feature engineering good clear instructions, and valuable content.
APIs cannot be activated and then cannot be used in the lab.Because of this I was unable to actually do many of the labs that required the use of the Google APIs including the keystone lab "Improve ML model with Feature Engineering" where the taxi-fare prediction model is refined into a perfected state.I'm upset that I paid money for this.
It worth to take 2nd times for practice in real world ML feature engineering.
This course teach how to do feature engineering is very useful in working Excellent course!
The course provides an overview and details of a very varied, comprehensive, and advanced range of possibilities to do feature engineering.
A highly sofisticated course about feature engineering and tensorflow union with tf.transform.
The subject is very interesting and I was alwyas curious about how Feature Engineering should be done with Tensorflow.
I come from Pandas, where feature engineering is not that difficult, but with Tensorflow it is different and not that intuitive.
Some missing steps in lab descriptions Best course to learn feature engineering this was really good, except removed one start for trifacta integration of dataflow lab.
Very good stuff on feature engineering overall.
Feature Engineering is critical.
Excellent Course and advice from experts about Feature Engineering and data pipelines utilizing advanced processes on GCP, thanks to Google and Coursera.
very nice course , -1 star for no pdf/ppt notes made available Had some problems with a few of the labs but the course was very informative Good to learn the Feature Engineering.
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apache beam
It's a pretty interesting course, specially that's the only one that teaches featuring engineering with a focus on production issues, but it assumes some knowledge with apache beam, and dataflow.
:) Some labs don't work The tf.transform and Apache Beam concepts are not explained in simple ways.
I would have liked a slower introduction to apache beam and more information about tf.transform I feel that this, and the tensor flow course that proceeds it in the specialization, were a waste of my time.
Its a graet course team me one of the most important took "Apache Beam" I defiantly use this in my upcoming projects.
I only give 4 star because of poor teaching by "Carl Osipov" Labs have problems Very well explained, lost time during tutorials because of apache beam version conficts with google cloud dataflow This wasn't a bad course, but it is more geared towards showcasing GCP features (BigQuery, Dataflow, Apache Beam, etc.)
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google cloud
Some of the labs had big query errors, and some of the google cloud interfaces changed, so careful when doing the labs, the options and the buttons may have been shifted or renamed In general, this course is very well prepared, covers a good piece of material and I'm leaving it with a lot of new things to try.
This course seems like more of an advertisement for Google Cloud Platform than feature engineering: details of engineering part is hardly covered in the course; more emphasis is on demonstrating on how to do it on GCP.
Thankyou coursera and google cloud Detailed explanations and examples.
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most important
One of the most important in this specialization.I learned a lot!
Probably the most important part of the specialization, and where I learned the most A lot of the code, did not work.
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machine learning
A separate course to emphasise the role and importance of feature engineering in machine learning is what really got to me.
Not directly applicable to where I am in my machine learning career, but good to know in the future, nonetheless... Hope all the materials in this course will be updated soon.
This module covers a lot of tricks that should be employed during preprocessing to improve the prediction accuracy of machine learning methods.
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rather than
Also, it would be great if some of the labs are more clarified and introduce more opportunities for students to participate in writing code for the lab session rather than just going through it and running existing code.
The presentations need some graphics rather than a guy talking.
The course focuses much more on the gcp tools rather than the feature engineering, labs were not easy to follow, some pieces of code did not work properly.
rather than teaching feature engineering.
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one week
course material for reference The work needed was waaaaay below a one week Felt like it was cut short at the end.
Too long for one week.
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best course
Best course content in this specialization!!
Best course in the series so far!
google apis
Ultimately I found this course to be disappointing, because the Google APIs for DataFlow, BigQuery, etc.
Two of the labs didn't work because the Google lectures aren't up-to-date with the Google APIs.
Careers
An overview of related careers and their average salaries in the US. Bars indicate income percentile.
Laboratory Technician (vertex Pharmaceuticals) $43k
Hitting Coach @ ML LEVEL $49k
Feature Film Casting $59k
Entertainment and Feature Writer $65k
Machine Learning Scientist, ML Platform $66k
Senior Feature Writer & Columnist $76k
Associate Feature Estimator $78k
Associate Feature Producer $94k
Senior Business Analyst from Vertex $96k
Manufacturing Engineer - ML ME Measurement $103k
Producer - Feature Animation $131k
Stepfather (feature) $156k
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| Rating | 4.0★ based on 126 ratings |
|---|---|
| Length | 4 weeks |
| Effort | 2 weeks of study, 5-7 hours per week |
| Starts | Jul 3 (43 weeks ago) |
| Cost | $49 |
| From | Google Cloud via Coursera |
| Instructor | Google Cloud Training |
| Download Videos | On all desktop and mobile devices |
| Language | English |
| Subjects | Data Science Programming IT & Networking |
| Tags | Data Science Machine Learning Cloud Computing Information Technology |
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