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Avis et commentaires pour d'étudiants pour Introduction to Machine Learning in Production par

1,652 évaluations
289 avis

À propos du cours

In the first course of Machine Learning Engineering for Production Specialization, you will identify the various components and design an ML production system end-to-end: project scoping, data needs, modeling strategies, and deployment constraints and requirements; and learn how to establish a model baseline, address concept drift, and prototype the process for developing, deploying, and continuously improving a productionized ML application. Understanding machine learning and deep learning concepts is essential, but if you’re looking to build an effective AI career, you need production engineering capabilities as well. Machine learning engineering for production combines the foundational concepts of machine learning with the functional expertise of modern software development and engineering roles to help you develop production-ready skills. Week 1: Overview of the ML Lifecycle and Deployment Week 2: Selecting and Training a Model Week 3: Data Definition and Baseline...

Meilleurs avis


4 juin 2021

really a great course. It'll really change your way of thinking ML in production use and will help you better understand how can you leverage the power of ML in a way that I'll really create a value


5 déc. 2021

I have been involved with deep learning for more than 5 years (in academia), nevertheless learned a lot already. I am very curious about the next courses. Thanks for putting together this course!

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126 - 150 sur 330 Avis pour Introduction to Machine Learning in Production

par Arian N

10 févr. 2022

Invaluable guidance on how to approach production-grade projects. Loved the course!

par Nitin M

30 mai 2021

Very useful and complex material made easy to understand by an excellent instructor!

par Nikolina K

1 juin 2021

Very useful topics covered! Andrew explains in a clear way, with a lot of examples.

par Dvdxnss

17 mai 2021

Excellent course, as always. That's a really good introduction to ML in production.

par AserGarcia

7 juin 2021

Great introductory course on the operations to keep a system afloat in production.

par Eddie M

2 avr. 2022

Very clear and concise, incredibly valuable knowledge and techniques. Thank you.

par Endre H

6 févr. 2022

The optional lecture was realy a good additional value of this course. Thank you!

par Steven I

28 sept. 2021

T​he flow of this course and explanation with examples, made learning quite easy,

par Susan M

25 juil. 2021

Have not yet competed labs - course in progress. Request for review premature.

par Gaurav P

30 août 2021

extremely helpful course, gave a deep insight of data-centric machine learning

par Nikhil K

3 juin 2021

Awesome course. Got to learn a lot of new things related to ML in Production.

par MohammadReza L

12 juin 2022

I like this course, it help me to have vision about ML development process.

par paul b

12 mars 2022

Yet another excellent well structured and informative course from Andrew!!!

par Shawn L

14 déc. 2021

Indeed a great course. It changes your way of thinking in Machine Learning.

par Shubham S

22 août 2021

Learnt a lot new and applicable concepts and practices. Highly recommended.

par Bob K

17 août 2021

Overall, an excellent and well presented introduction to ML in production.

par Viraj H

31 oct. 2021

It is quite good course I learned a lot of basic things from this course.

par Zoran H

25 juin 2022

It is a nice introduction to MLOps segment general terms and background.

par Ghada S

11 janv. 2022

Very insightful course. Many thanks for all the provided efforts over it


20 avr. 2022

Learned some basics of MLOps and terms in this course. Looking forward!


20 sept. 2021

This Course covers all the basic practical aspects about ML Production.

par Juan A

19 mai 2021

Very Excellent Course. Allows me to seek and dig deep into the ML World

par Aymen S

7 juin 2022

The is a very good introduction course for this amazing spezialisation

par andre m

14 juin 2021

Amazing course, theory based on experience. Lessons that no book have.

par Hoang V

6 juin 2021

O​nce of the best! I learnt a lot of useful insights from this series