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Opiniones y comentarios de aprendices correspondientes a Introduction to Machine Learning in Production por parte de

1,673 calificaciones
294 reseña

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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...

Principales reseñas


4 de jun. de 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


14 de ago. de 2021

Excellent course, as always. Very well explain for both Data Sicientist, Software engineer and Manager (with some basics undertsanding of ML). One of these courses that Data Sientist should follow.

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301 - 325 de 332 revisiones para Introduction to Machine Learning in Production

por Justin L

7 de jun. de 2021

S​o far this course has been pretty great. Nifty Labs with a lot of useful info and methods.

por Davide V

24 de jun. de 2021

Quite basic, but still useful introduction to following courses of the specialization


11 de oct. de 2021

Useful course for understanding how ML works in production in an iterative approach.

por Ahmed M A

1 de jul. de 2021

Very comprenshive course summarizes the concept of Data-centric approach in MLOps

por Myrzakhan N

6 de jul. de 2021

T​his course was very useful on planning ml model deployment lifecycle!

por Jaret A

1 de jul. de 2021

Very interesting, a lot of new little concepts. I enjoy Andrew's tips.

por Umberto S

23 de jul. de 2021

Really clear explanation about foundamentals of ML in real world

por Dong P

27 de dic. de 2021

Great course for establishing real Machine Learning projects

por Christian K

22 de jun. de 2022

The content is great, but it could be condensed a lot!

por Sudip C M

25 de mar. de 2022

G​ood intro course on machine learning for production

por Timothy G

10 de jul. de 2021

Learn some additional information Mlop

por changfuli

6 de jun. de 2021

Would be great if comes with more labs

por Kepchyck

22 de mar. de 2022

It's cool, but it isn't for begginer

por Simon A

27 de jul. de 2021

Great, but needs more content !

por Maria E

26 de ene. de 2022

use a more hands on approach.

por Mayank A

19 de jul. de 2021

build foundations for MLOPs

por Arman S

20 de abr. de 2022

Good foundational course

por yeison d

13 de sep. de 2021

Amazing intro course

por Javier P O

8 de abr. de 2022

Great introduction!

por davecote

18 de ene. de 2022

light but usefull

por shushanta p

1 de ago. de 2021

Excellent course

por Ernesto A

8 de jul. de 2021

Ernesto Anaya

por Enrique C

4 de ene. de 2022

Good intro but it looks like in other courses from, while they teach you something, they also try to "sell" people a specific framework. In this case, they seem to be selling TFX. I still recall how they sold people the Trax library in the NLP specialization which has replaced Trax with huggingface. I take what is useful from these courses but I distrust their agenda.

por Diego L

9 de jun. de 2021

It is really a nice conversation with Andrew Ng over some problems that you face when you try to put model on production, define projects and manage it. But, the frameworks that he proposes are totally general and this course has technical debts.

por yukongliang

3 de oct. de 2021

boring and kind of wasting time. I mean, learning course 2-4 is enough ,why there is an extra "outline" course here? Also, the content is a duplication with Andrew's other courses in coursara.