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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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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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51 - 75 de 354 revisiones para Introduction to Machine Learning in Production

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 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 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 Andrei N

12 de jun. de 2022

G​ood intro on key concept in MLOps. Would recommend it to anyone who is stepping into this field as well as for ML Hobbists to understand the main challenges of a ML production system

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 Di W

13 de feb. de 2022

Wonderful and practical MLOps introductory Materials. Very systematic and useful! Always appreciate Dr. Ng uses the most easy to understand language to explain difficult problems

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 Muhammad I K

17 de abr. de 2022

An excellent start for becoming a Machine Learning Engineer where one learns about the complete lifecycle of a machine learning project from scoping to deployment to monitoring.

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

por Jungwei F

13 de jun. de 2021

T​he course helped both validate what I knew about the topic and update me about many new trends/tools via high quality references + first hand experences from the instructor.

por Furkan T

2 de jul. de 2022

I think this course is great. I started to understand the importance of a data-centric approach. Thank you for everything Prof. Andrew. I can't wait to start the next course.

por Christian L C C

14 de jun. de 2022

A​ course that extends your vision about machine learning in production and helps you to understand that training a model and getting it with a good accurate is not enough

por Daniel H G

31 de ago. de 2021

Excellent course, you learn about the fundamentals of MLOps. A recommended course if you want to understand the life cycle of a Machine Learning algorithm in production.

por Stefano D P

19 de feb. de 2022

Concise and straight to the point! It is a good and broad introduction to the topic. I'm confident it has prepared me well for the next course of this specialization.

por Sadashiv B

24 de oct. de 2021

This course is fantastic. Exceptionally well understanding of all the fundamental concepts required. Many issues that one would not have considered are well-covered.

por Ratha P

3 de ago. de 2021

A great course that Andrew provided to fill the gap between machine learning/AI in academia (model-centric approach) and industry production (data-centric approach).

por Rodolfo T

2 de mar. de 2022

Great course with wise tips and insightful recommendations. I'll get to provide more value to the machine learning projects I'll have be involved after this course.

por Will G

7 de abr. de 2022

This course helped me land my first job as a data engineer. I am very glad to be a participant and student of Andrew Ng. I can't wait to finish its specialization.

por Nikki A

11 de ene. de 2022

Very well explained, Andrew Ng does a great job as always summarizing complex subjects in easily digestible lectures. A lot of thought went into this course

por Martin T

2 de dic. de 2021

Very useful discussions and views. Great reflections on the value of data in the full ML cycle and the real challenges of putting a ML system in production.