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Voltar para Structuring Machine Learning Projects

Comentários e feedback de alunos de Structuring Machine Learning Projects da instituição deeplearning.ai

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41,109 classificações
4,573 avaliações

Sobre o curso

You will learn how to build a successful machine learning project. If you aspire to be a technical leader in AI, and know how to set direction for your team's work, this course will show you how. Much of this content has never been taught elsewhere, and is drawn from my experience building and shipping many deep learning products. This course also has two "flight simulators" that let you practice decision-making as a machine learning project leader. This provides "industry experience" that you might otherwise get only after years of ML work experience. After 2 weeks, you will: - Understand how to diagnose errors in a machine learning system, and - Be able to prioritize the most promising directions for reducing error - Understand complex ML settings, such as mismatched training/test sets, and comparing to and/or surpassing human-level performance - Know how to apply end-to-end learning, transfer learning, and multi-task learning I've seen teams waste months or years through not understanding the principles taught in this course. I hope this two week course will save you months of time. This is a standalone course, and you can take this so long as you have basic machine learning knowledge. This is the third course in the Deep Learning Specialization....

Melhores avaliações

JB

Jul 02, 2020

While the information from this course was awesome I would've liked some hand on projects to get the information running. Nonetheless, the two simulation task were the best (more would've been neat!).

MG

Mar 31, 2020

It is very nice to have a very experienced deep learning practitioner showing you the "magic" of making DNN works. That is usually passed from Professor to graduate student, but is available here now.

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126 — 150 de 4,542 Avaliações para o Structuring Machine Learning Projects

por Rashmi N

May 19, 2019

Thanks a real bunch, Coursera for providing financial aid and bringing up this course, truly loved each and every section, coupled with quiz section at the end, is so much helpful and of course, very thoroughly made! Thanks to all the hardworking instructors and teaching assistance, and of course, coursera team for making this course so effectively! :)

por Sikang B

Apr 01, 2018

Generally felt this course is super useful as it helped answering several questions of "why we do things this way" rather than follow the paradigm of "it just magically works". Though there are still many magic moments while learning on ML in general, I felt this course really helped broad my view and understand the overall problem space much better.

por Luo D

Sep 15, 2017

Having finished the first three courses in the Deeplearning.ai's specialization, I find this course is the most valuable one. It is not telling you the basic algorithms like the first two courses, but telling you how to ANALYZE you project as a whole in each step, and where to go next. The first two tell you how to build, this one tells how to THINK.

por Jay C

Mar 20, 2018

Excellent guide work by Andrew NG,

I really like the way he delivers the intuitions or insights from deep networks. The most important think when working with these kind of project is to look below find what you missed in considering higher level extraction. I'm really inspired by his work and keep the advice to improve performance for all projects.

por Abdelrahman R

Feb 12, 2020

Maybe its different and should help us not just thinking of Algorithms and models ,we should think out of box and think of the error from different approaches as human relative to the machine, think of the data we have, think of different distribution of the data, trying to knowing with different approaches how we should care about of these error.

por Yiyou L

Nov 13, 2017

This is a very good course. Worth taking. I am currently a data scientist and in my daily work I face a lot of data mismatch problems and I have no idea what to do after error analysis. This provides a very good guideline of how to structure our deep learning projects and what should be the thinking logics behind. Thank you Andrew I really love it.

por Nitin G

Nov 15, 2019

Have taken a formal 1 year course from a prominent Institute but these kind of concepts were never covered there. The beauty of this course and all courses by Andrew Ng is that they are so simple and easy to understand that one can't help but only understand the concepts. Best methodology and delivery of teaching I have found online. Thanks a lot.

por Kanwal

May 11, 2020

Excellent course and well presented material. I would like to recommend all the ML engineers to review this course before starting actual development. This course explains different intuitions and techniques with reasons what to choose, where to apply and when to apply.

Great course. Enjoyed a lot. Thanks Andrew for your precious time and efforts.

por Urso W

Sep 08, 2017

Having followed this course I have learned how to address common problems that I have found in the evaluation of performance of my neural net based on fed datasets. I am now able to reason much better (thoughtful) on the problems that I encounter having learned some error analysis techniques which have been addressed in this course. Thumbs up!

por Ondrej T

Dec 25, 2018

I really liked the programming assignments in the two previous courses (although, it was usually not enough challenging for me). In this course, I found "case study" assignments very useful and exciting. So far, I am very satisfied with the DeepLearning Specialization; I will definitely continue to the 4th and 5th course. Many thanks for it!

por Li-Han C

Dec 12, 2019

I thought it's a trivial course and I didn't expect that much. HOWEVER, I must say this is one of the most important courses EVER in ML. SO MUCH I should larn before doing my dissertation. I really don't need to DIY so many things. Thank you, teacher Andrew for sharing the treasure experience. I really learn many concepts from your lecture!

por Oly S

Jul 07, 2019

Wow. This course is densely packed with really great *practical* and well-justified advice, based on Prof. Ng's extensive experience. There's lots of wisdom here for taking the step from understanding 'in principle' how machine learning can be applied, to having practical understanding of the techniques to get it to really work in practice.

por Alejandro S M

Feb 17, 2018

Very interesting course to avoid common pitfalls and have already some developed intuition without having worked in any ML project before.

The case studies in the quiz are extremely helpful as some concepts can be a bit confusing and they help clarify the doubts you might have in the subtleties between the different situations you may find.

por Carlos V

Dec 26, 2017

"Structuring Machine Learning Projects" provide so many good practices in how to correctly implement Deep Learning Models, troubleshoot them and make them better, the tips and recommendations are excellent, highly recommended to anyone interested in deep learning this is a fantastic Course, thanks to everyone that make this Course possible.

por Reza M

May 11, 2020

When you deiced to join AI teams, you need to tackle out-of-the-blue and state-of-the-art problems. Managing this kind of situations aren't easy and need different tips and tricks based on the problem statements. This course come up with brilliant ideas to make up your mind in these challenges. Great job! Coursera and deeplearning.ai

Thanks

por Shivdas P

Dec 25, 2019

This course gives a very intuitive understanding for analysing performance of neural networks and strategies to go about improving them. Also liked the introduction for Transfer Learning. The quiz which was kind of a pilot simulator for machine learning project, is excellent in understanding the decision making process for such use-cases.

por Rahul K

Mar 01, 2018

Really well structured material! Don't be fooled by the lack of assignments, though; this course is pretty theoretically challenging. Pay extra attention to all the data distribution lectures - they are bound to come in handy in practical use. I learnt tons of really useful information from this course. As usual, hats off to Prof. Andrew!

por Raimond L

Aug 23, 2017

This course provides a lot of interesting topics, which are general things to understand before taking on any deep learning project. I highly recommend listening to this course. It widened my view on projects I work on.

Quizzes on the other hand are bit of a mess on this course (however they are giving enough challenge to apply the theory)

por Sriram V

Oct 09, 2019

Another set of insightful patterns from Andrew' (as well as his team') experience was stitched well together. Definitely, most of the discussions were thought-provoking for someone who is late entrant in this space. Some more reading (optional) could have added to enable us to understand more common problems in Machine Learning projects.

por Utkarsh P

Mar 11, 2019

This course is extremely valuable for any Machine Learning student. It covers a lot of important concepts that need to be used even for simple ML tasks (not deep learning). This course provides a framework to iterate on your problems and I believe that will make the most difference in how fast you are able to achieve desired performance.

por Rishubh K

Mar 14, 2018

Really unique content. People do talk about this stuff but providing access to these learnings in a structured manner i amazing. I feel I could now lead my efforts in DL project much more efficiently. I felt the case studies were amazing. I wish we had more of those available to us to practice. But, nonetheless, great work. Thanks much!

por Subhasis M

Oct 12, 2017

This is an excellent overview of the points that someone taking up an ML/DL project should keep in mind. Though this is not a comprehensive guide, which is understandable given the stipulated duration online courses like this are meant for, this is a definitive guide to give someone a nice head start into structuring his ML/DL project.

por Dmitry R

Apr 15, 2020

This, in my opinion, is the most important course in the specialization! It teaches you how to plan your machine learning project, which errors and challenges can rise during implementation and how can you deal with them. Personally, I feel it helped me a lot as I currently try to plan my machine learning project as part of my thesis.

por Fasih U

May 26, 2019

I learned a lot about different strategies to chose for getting fast and much better out come from this course. Also downloaded the book mlyearning written by Dr. Andrew. So that i will have all this in my hand when i will need this strategies to review. Thank you Andre Ng for giving this much information. You are the best I love you.

por Ankit K

Mar 12, 2019

thanks for providing good insights on how to approach a machine learning application and where not to waste valuable efforts. I think Mr Ng has been very thoughtful to setup the structuring part as a dedicated course which highlights the importance of setting right goals and not to lose our direction during the development iterations.