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Machine Learning in the Enterprise(으)로 돌아가기

Google 클라우드의 Machine Learning in the Enterprise 학습자 리뷰 및 피드백

1,402개의 평가

강좌 소개

This course encompasses a real-world practical approach to the ML Workflow: a case study approach that presents an ML team faced with several ML business requirements and use cases. This team must understand the tools required for data management and governance and consider the best approach for data preprocessing: from providing an overview of Dataflow and Dataprep to using BigQuery for preprocessing tasks. The team is presented with three options to build machine learning models for two specific use cases. This course explains why the team would use AutoML, BigQuery ML, or custom training to achieve their objectives. A deeper dive into custom training is presented in this course. We describe custom training requirements from training code structure, storage, and loading large datasets to exporting a trained model. You will build a custom training machine learning model, which allows you to build a container image with little knowledge of Docker. The case study team examines hyperparameter tuning using Vertex Vizier and how it can be used to improve model performance. To understand more about model improvement, we dive into a bit of theory: we discuss regularization, dealing with sparsity, and many other essential concepts and principles. We end with an overview of prediction and model monitoring and how Vertex AI can be used to manage ML models....

최상위 리뷰


2018년 12월 30일

thanks for the great work. There is so much to learn and I appreciate the effort you made to break things down and providing lab while making the hard decisions on what to commit.


2020년 6월 6일

This course is so really good to learn about the general knowledge and skill of Data Science like optimization batch or regularization and so on with Google Cloud Platform.

필터링 기준:

Machine Learning in the Enterprise의 119개 리뷰 중 1~25

교육 기관: Eric S

2019년 2월 1일

It has a lot fo great content, but the way it's laid out confused me greatly.

It also felt very rushed at times, many parts weren't explained in detail, making many parts much less educational than I feel they should've been.

The best parts are where Lak is presenting, even in the lab solutions he went to more details than anyone else and made even those videos interesting after solving it myself.

교육 기관: Dmitry B

2019년 5월 6일

The quality of the lesson material is great but the quantity is nowhere sufficient to get the hands-on experience

교육 기관: Luciano M

2019년 1월 13일

Labs were had less quality than in previous weeks.

교육 기관: john f d

2018년 7월 18일

Labs vms are to slow. Speaker is difficult to understand. Mic varies and speech pattern is not clear. The presentations need some graphics rather than a guy talking. Sketch out the ideas on a white board rather than talking 5 minutes to a single slide.

교육 기관: Soham M

2018년 10월 12일

The best course ever to give you the glimpse of the whole ML land - what is ML? Why ML? and most importantly How to do ML for real life business problems - from developing models to model evaluation, serving in production with all scaling tips and techniques with essence of Cloud. The best course for ML practitioners out there. Learnt a lot and what other place to learn from apart from the people who are actually doing it for the most popular products used across the web and mobile world.

교육 기관: Jun W

2018년 5월 29일

This final course is also very good. Embedding is my favorite part and Lak is my favorite instructor.

Thanks Googlers! Looking forward to the next five courses.

교육 기관: Cooper C

2020년 1월 22일

My feeling is that this entire specialization is a glorified demonstration of what GCP can do with ML. The labs are not interactive and in some cases did not work. I don't feel that I have learned anything new. If I were to use GCP for ML purposes, I would need additional training to do it. I don't recommend this specialization

교육 기관: Laimonas S

2018년 12월 2일

Too shallow to truly be useful. I think if anything it gives you an idea of what's possible and roughly the areas you should explore and learn about but you won't learn too much following this through.

교육 기관: Dimitry I

2019년 11월 14일

Good course, but I couldn't get over the Estimator API. IMHO it's too complicated compared to Keras and I just could not force myself to care about it.

교육 기관: Yakup K Y

2019년 5월 20일

Some lab contents are distracting from the core subject, deviate from the video contents.

교육 기관: Badhan S

2020년 5월 8일

I have learned a lot of things about Machine Learning from this course. Thanks, Google Cloud team form this awesome course. Actually there are many Machine Learning courses or articles out there. But nobody tells me what is the best way to do one thing, why I will use this step for certain things. If anyone tells but he could not show the proper visualization, it is the correct way to do so. Now I will be participating in real-life projects to apply what I learn. If I get stuck then I will use this course as my reference guide.

교육 기관: Patrick M A

2018년 9월 2일

This course goes deeper into how to improve your Tensorflow ML models' performance without going deep into the models themselves. A good intro to learn how to systematically tune hyperparameters like the learning rate or batch size, and also how to start using regularization techniques and embeddings. Finally the course also opens the door to custom estimators, keeping you interested for the next courses.

교육 기관: James W

2019년 9월 27일

Good class with a lot of information and new terminology thrown at you. Especially if you don't have a machine learning background. The labs are done in a way where you can get familiar with TensorFlow and Python programming, without having to know Python programming. Good intro if you want to be familiar with GCP ML. If you're looking to write a bunch of code this will probably not be enough for you.

교육 기관: Harold M

2018년 9월 27일

This is one of the best courses in this specilization, as it goes deeper in the internals of ML and Neural Networks. Also, it presents two important features such as Embedding (creating sparse tensors from features) and Custom Estimators, which is the first step to get into advanced topics such as implementing new estimators from Research Papers.

I've really leveraged from this course a lot.

Thank you!

교육 기관: Ertu S

2018년 9월 4일

The only concern is that There are lots mention of Batch Normalization however nor instructor neither lab exercises point out how to do proper Batch Normalization using Tensorflow. It seem like they suggest manual scaling. Also best to include a section how to use TensorBoard to fine tune training properly. Not clear how to monitor and correct training parameters thru TensorBoard.

교육 기관: Juan P D P

2018년 10월 20일

ML is a very rich topic with many paths to achieve a goal, that is important to differentiate because there is so much information people can get confused, this course focus helps to understand the topic. Labs range from basic to difficult and requires your full attention, there is still room to learn from other theorical sources.

교육 기관: zios s

2019년 11월 29일

Great course for understanding in and out of Machine learning model. I learn lots of cool thing in it. Most important I learn about Google Vizire: A great tool for hyper parameter tuning. Now I am starting "Advanced Machine Learning with TensorFlow on Google Cloud Platform Specialization".

교육 기관: Linh D

2020년 4월 8일

Good class with a lot of information and new terminology thrown at you.

The labs are done in a way where you can get familiar with TensorFlow and Python programming, without having to know Python programming.

Awesome intro if you want to be familiar with GCP ML.

교육 기관: Mario R

2019년 1월 13일

Great course! You get some basics on how to fine tune your model (and why those methods are effective). Nice introduction to NN and what I think was the most relevant: building estimators from scratch and how Keras can offer a simpler way to work.

교육 기관: Jafed E G

2019년 7월 6일

I enjoy the lectures. The professor has a good speaking and teaching style which keeps me interested. Lots of concrete math examples which make it easier to understand. Very good slides which are well formulated and easy to understand

교육 기관: Abdur R M

2018년 10월 2일

The best course of the specialization. Drills right into the heart of ML in terms of how to improve your models and also shines some light on how to create custom NN models which can be used with all of the prebuild functions of TF.

교육 기관: Nicolas S

2020년 4월 19일

Some issues wit the Google Cloud Plateform (UI bug, instabilities). Aside that, the course is great and well built. Although I already knew ML theory, I learnt few tricks about implementation and running model at scale.

교육 기관: Ayush T

2019년 9월 6일

This course is of specialization is the most applicable in the case of my work. If customer estimator was explained in the earlier courses, many other experiments with our own custom estimators could have been tried.

교육 기관: Mr. J

2019년 8월 27일

Now that's what I am talking about. Great survey on nuts and bolts of ML practicalities. The how and why of model generation and manipulation. Very excellent. Super library of reference models and materials.

교육 기관: PLN R

2019년 1월 31일

Amazing way to keep the audience interested. Throughout the specialization, I was always interested to learn what was about to come, next up. I completely recommend this specialization. It is a fun way to learn!!