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Avis et commentaires pour d'étudiants pour Machine Learning in the Enterprise par Google Cloud

1,401 évaluations
121 avis

À propos du cours

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....

Meilleurs avis


30 déc. 2018

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.


6 juin 2020

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.

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101 - 119 sur 119 Avis pour Machine Learning in the Enterprise

par Attila B

20 déc. 2018

Really good course with a lot of practical examples.

par Pratik S

21 oct. 2019

complete hyper parameters is given in lab

par Ruslan A

16 août 2019

Many notebooks contain some typo/erros.

par Wang Y

29 oct. 2018

best course in the specialization!!!

par Gaurav B

13 févr. 2020

I was looking for more hands-on.

par Sarwar A

23 févr. 2021

Good course overall

par Swaraj P

10 mars 2019

Nice tutorial

par KyeongUk J

28 oct. 2018


par Matthew B

29 juin 2019

Labs were very confusing. Explained theories well but in practice didn't really learn much. I wouldn't recommend if you're a beginner. Google has a very interesting way on teaching.... On that note they should stick to building tech, never teaching. Didn't really learn how to build anything in ML, sort of skimmed on some API's they offer. In reality, the first course was probably the best... The rest of the specialization was just a rinse and repeat sort of thing.

par Bhargav D

26 avr. 2020

Great course must should make labs compulsory and not provide solution it takes away the fun of thinking.

par Siddharth A

9 nov. 2018

I felt that hand-on or explanation was not sufficient. Coverage is good.

par Alberto C

23 oct. 2018

There are some lessons where the concepts are exposed in a too fast way

par Rahul K

5 mai 2019

Some tough concepts !!!

par Pablo I F

5 août 2020

Very bad english subtitles. For non-english speakers, the subtitles doesn't help, but it confuse what the teacher is explaining. It takes me a lot of time to understand some parts of the course

par Mike W

22 juin 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.

par Arman A

11 avr. 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.

par Mohannad B

13 août 2020

A lot of inaccurate data, please check deep learning ai specialization for more accurate info. this is good for introducing you to GCP not the concepts of AI

par Radha M K V

29 déc. 2019

Very redundant and superficial.

par man c y

26 juin 2019

poor labs