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

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Acerca del Curso

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

RG

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

TF

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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326 - 350 de 354 revisiones para Introduction to Machine Learning in Production

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 Baurjan S

15 de jul. de 2022

It's a great introduction course. But excessively easy.

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 deeplearning.ai, 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 jitao f

6 de ago. de 2022

I have worked in AI powered healthcare imaging industry for some years. Most of concept mentioned are our daily routaine. It is good to catch them up with constructed courses but I was expecting more juciy.

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.

por Kenan M

11 de mar. de 2022

Consice and Vocational , especial to those working on unstructured data. I enjoyed it. Thanks

por Ravi A

11 de ene. de 2022

G​ood overview of best practises, but still a bit too general and non-technical.

por Matthew A

8 de dic. de 2021

It seemed a little too general. I would've liked more labs.

por diego p

20 de jul. de 2021

Much more a high level course respect to what i expected