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

4.8
estrellas
1,220 calificaciones
221 reseña

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

IU
5 de dic. de 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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26 - 50 de 251 revisiones para Introduction to Machine Learning in Production

por Baturalp M

30 de may. de 2021

Great for beginners but I also ejoyed it since it nicely tidies the practical knowledge that an experienced ML engineer/data scientist gains throughout his work. Overall, it's a good polishing over my knowledge and learned some new points that I didn't paid enough attention to.

por Mindset N

16 de jun. de 2021

This course is very hands-on. It clearly teaches Machine learning beyond python notebook. I enjoyed this course and currently taking the second part of this specialization "Machine Learning Data Lifecycle in Production". Great content from Andrew Ng and Robert Crowe.

por Shekhar S

30 de dic. de 2021

It's really refreshing to see the "behind the scenes" perspective on ML algorithm development. Although I have been working in Computer Vision for more than 10 years, I found Andrew's frameworks to think about the project lifecycle and data very useful. Thank you!

por Carlos A L P

4 de nov. de 2021

Great theorical material to understand ML projects. The 1st (ungraded) lab exercise was not very clear though when playing with the front end and back end application, it would be nice to provide more information or tips on how to complete it

por Hernán Q

23 de jul. de 2021

It covers a lot of the real world problems data scientists find when trying to build machine learning solutions. Many of the best practices reviewed here are a common sense thing but having it wrapped toghteter here was really great !

por Nilesh G

26 de jun. de 2021

Deep learning courses are always best, cover all aspects in theoretical as well as more emphasize on practical knowledge which helps a learner ready for the real life challenges in Data science domain...Thank You Andrew NG and Team

por Iosif D

17 de oct. de 2021

A​mazing introductory course that gives you the full scope immediately, as well as many theoretical details on each section. I expect the following courses of the specialization to dive into more technical things and frameworks.

por Paulo A A M

26 de jul. de 2021

Excellent course!! A new way to understand the key factors to master the Machine Learning lifecycle. This is much more than one course, this is an invitation to change our mindset through an exciting journey with Andrew Ng!!

por Taku F

6 de jun. de 2021

The course was fairly compact and you would be able to finish each week lesson every day if you eager to do so. It was fun and educational. I loved the surprise in the last question of the optional quiz in week 3.

por Motilal R S

13 de jun. de 2021

Great course explaining concepts on ML lifecycle and deployment, especially touching topics like concept and model drift, monitoring models, error analysis, experiment tracking, pipeline and lineage. I loved it.

por ChenChang S

23 de jun. de 2021

This is a great introduction for how the mature machine learning product could be morph into mature products with multiple challenges. It helps me a lot for understanding how future AI industry looks like !

por Daniel Y

17 de dic. de 2021

This course would be very useful if you are ML-engineers, data scientists. However, this course does not teach you how to code. To code, you need to take Deep Learning specialization or some other courses.

por Xiaonan S

23 de sep. de 2021

Very practical materials and application-focused methodology! A lot of rule-of-thumb gathered from ML pipeline experiences. Clear definition on acronyms and mainly easy-to-follow non-technical guidances.

por Hector B

11 de jun. de 2021

Very valuable course for those who already have some knowledge on machine learning or AI applications. Very close to what systems engineering processes recommend, as when seeking ISO15288 compliance.

por Dr. F T

15 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.

por rahul g

5 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

por ismagil u

5 de dic. de 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!

por Nilay

12 de jul. de 2021

I​ntroduces you to the basics of MLOps in a well paced mannar. Would request to add more examples of structured data sets, as many companies usually are dealing with the related problems.

por UGENTERAAN A L M

5 de jun. de 2021

The content of this course has been especially useful for me. I wish there were more emphasis on the tools recommendation as well, but the theoretical knowledge was just fine. Thank you!

por dongkyoung c

21 de may. de 2021

Practical and well-structured advices throughout the lifecycle of ML. Examples from real world problems & experiences make the advices more tangible and helps to reflect on own problems.

por Elga

20 de may. de 2021

Excellent course, as always! Many thanks!

Great combination of theory + notebooks with practical examples.

Everything is perfectly structured. I will recommend this course to everyone!

por Gent S

26 de may. de 2021

Andew Ng is truly a world leader in the field, the way he approaches the subject and the explanations he gives are truly unparalleled. It always a pleasure taking a course he instructs.

por Alejandro M R

19 de may. de 2021

This is a great course to learn many practical procedures and techniques, to apply ML algorithms to real world problems and do it well, by avoiding common mistakes and deliver value.

por Ilce M

20 de jun. de 2021

I would recommend this course to anyone who has to implement models in production. It is an introductory course but it does have a few key concepts that are good to keep in mind.

por Pawel R

25 de may. de 2021

This course helped me to organize my knowledge, and showed the questions that I should regullarly ask to either technical, or business teams to create valuable AI-based product