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

1,253 calificaciones
223 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

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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1 - 25 de 256 revisiones para Introduction to Machine Learning in Production

por Francisco R

21 de may. de 2021

I know it's an introduction, but I got a bit disappointed. It's quite basic and even though it has some hands on notebooks, they're optional and you don't need to work on anything. Quizzes are easy, and I didn't have the feeling I learnt much. I'm still rating it with 3 because, well, it's Andrew Ng, and this his teaching is worth gold.

por Snehotosh B

22 de may. de 2021

I found the production part absent and is another ML course.

por Mohamed A H

14 de may. de 2021

I give you the full review stars since I learned many new things that I did not pay attention to before, e.g.: I used to focus on models for many years instead of data.

por Rajesh R

22 de jun. de 2021

Most of the discussion was theoretical. Some useful knowledge but not useful for real world MLOps

por Picioroaga F

13 de jul. de 2021

This course was one of best that I've taken regarding the ML. I think this course should be the starting point for each student who would like to pursue a career in ML and AI. Understanding the problem in the business context before jumping to the solution, understating the data in the same context, are the key ingredients for defining the success of a "product/service" involving AI.

por HARI A K

16 de may. de 2021

Really good for anyone with strong background in DL and ML... And want to be able to start a real time project... Or lead a ML team

por Kyung-Hoon K

16 de jul. de 2021

Thanks, Andrew!!!!! Your sharing real-life experiences was invaluable. This was super special as it has opened my eyes beyond the ML-code. I've realized what I have to do in my real job. I will spend more time on communicating with business teams to close the gaps on different metrics expectations. I will shift my mindset from code-centric to data-centric. I will check out my data before my team dives into the ML coding itself. Thanks, Andrew and the team!!

por Omar A

20 de jun. de 2021

I liked how Andrew is able to simplify difficult and tricky concept without making you feel uncomfortable about lacking the knowledge. Everything is smooth and up to the point. In addition, the labs are interesting and highly related to the material. Overall, the concepts taught are very helpful and important to make you an real machine learning engineer not just a one who copy and paste bunch of theories, codes, ....etc.

por Bhargav U

30 de sep. de 2021

If you have work on industry projects, you must have come across such scenarios described in the course. This course provides a structured way to analysis different situations arises during a ML project life-cycle and teaches way to make decisions which increases the chance of success. It is really helpful.

por Gaurav G

23 de may. de 2021

Awesome Course.... :) Really I enjoyed a lot. I completed this 3 weeks of course just in 4 days along with my office work (too much interesting).Very helpful... Very knowledgable... Thanks Andrew Ng for the course. A big thank to DeepLearning.AI team.

por Cristiano G

11 de jun. de 2021

Very nice course! The field of MLOps is not so well documented and fortunately we have very experienced professionals able to share their expertise. The content is very clear and the examples provided by the professor are extremely insightful.

por Wesley E B

16 de may. de 2021

It had some great advice for how to design a machine learning system. More practical examples would have been appreciated.

por Tamim-Ul-Haq M

13 de jun. de 2021

Incredible course. It describes in detail of how machine learning engineering is done in a production environment. It takes the aspects learnt for Course 3 (Structuring Machine Learning Projects) from the Deep Learning Specialization (also taught by Andrew Ng) and provides an even more in-depth knowledge base

por Engin K

11 de sep. de 2021

T​he course goes through methods to solve common operational problems that data scientists experience all the time but are not either aware of the problem or do not know how to solve the problem. All the methods are explained clearly with some practical examples. One of 'must take' courses by Andrew NG.

por Dennis D

21 de may. de 2021

Even after having worked several years in the role of an MLE there were some useful ideas here and there that I'm excited about applying in the future. Overall, everything was very clear and understandable. I liked the lab about deployment.

por Anand V S C

9 de jun. de 2021

I have been working in a large payments technology company for last one year and I can vouch for all the processes Andrew beautifully summarised. It does help a lot working in the industry.

por Deepak K

14 de may. de 2021

it was good to learn

por Koke H

3 de jun. de 2021

All pretty trivial

por Wenjuan C

20 de sep. de 2021

I had a great time learning with Andrew in this Introduction to Machine Learning in Production online course. In 3 weeks, Andrew walked me through each step in the machine learning project lifecycle and shared many best practice tips (from years of experience of his own), which I felt could be directly adopted and applied.  I especially appreciate Andrew’s emphasis on a data-centric approach and raising human-level performance. There are two valuable and practical suggestions to increase your machine learning model accuracy and contribute to a successful ML project, which have not been given enough importance in practice. As always, Andrew’s friendly, clear, and concise style and his capability to explain complex ideas with simple language made some of the seemingly intimidating subjects easy to digest. 

por Suneha K S

26 de sep. de 2021

This course acts as a very good guide in helping one improve the most important thought-process aspect of the project development, that's vital to work in the field of ML and AI. There are countless videos and tutorials on the internet today, that will help one learn the technical skills. But this course provides a shortcut to learn thought/project development process aspects which are usually gained only through years of experience. The best part was, all the concepts have been explained by taking a real-world use case, which makes the discussions non-trivial and practical.

por Brad D

15 de dic. de 2021

Andrew Ng presents a very thoughtful and insightful look at production issues in machine learning. His insights answer a lot of the questions I had after finishing a bootcamp elsewhere, although I might not have been prepared to understand everything he said if I had not taken that bootcamp.

His tone is very reassuring and intellectually stimulating, despite pronouncing all 'c's with a 'z' sound. :- }

por Keith K

5 de jul. de 2021

I found that the course is quite useful and practical. I enjoy a lot watching Andrew's Lectures especially when he used many examples from his previous projects in his career , giving good demonstration of common challenges in ML model development as well as maintenance/monitoring in production. The course is well designed and gives us a very clear foundation about Machine Learning in production.

por Muhammad D

22 de jul. de 2021

I find this to be a very philosophical approach to Machine Learning, especially where Andrew NG poise questions that will make you rethink entirely the way you've previously approached ML Problems. The explanations are broken down in a manner that makes it so seamless to grasp. Thank you for this opportunity.

por Jaime A D

4 de ene. de 2022

Genial, es un gran curso, 100% recomendado. Es difícil, incluso en escuelas de posgrado, encontrar un curso que cubra estos temas en Latinoamérica. Los temas que se abordan aquí sin duda tendrán un gran impacto en los próximos años. ¡Gracias por democratizar el conocimiento y ponerlo al alcance de todos!

por Abhilash G

10 de ene. de 2022

The whole specialisation is the best place to start if you are looking to productionize your machine learning models. The way they put forward each and every concept of MLOps life cycle will be a big eye opener, for people who are taking your machine learning models to production.