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Learner Reviews & Feedback for Structuring Machine Learning Projects by DeepLearning.AI

4.8
stars
44,159 ratings
4,979 reviews

About the Course

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....

Top reviews

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!).

AM

Nov 23, 2017

I learned so many things in this module. I learned that how to do error analysys and different kind of the learning techniques. Thanks Professor Andrew Ng to provide such a valuable and updated stuff.

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151 - 175 of 4,925 Reviews for Structuring Machine Learning Projects

By 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.

By 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.

By 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

By Raja S C

Oct 05, 2020

The concepts taught in this course are giving very basic foundations which are essential to build deep learning career. I no longer scared to talk confidently about a model in terms of bias, variance, error etc. Though this course was scheduled for 2 weeks, because of interest that it created, I am able to complete it in a day. Thank you.

By 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.

By 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!

By 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)

By 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.

By 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.

By 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!

By Marcio R

Aug 21, 2020

Excellent course overall! The course structure is very well made, Andrew is an amazing teacher and explains everything in a very detailed and intuitive way. The tests are a great way for practicing what was explained in the lectures. Strongly recommend this course to anyone interested in the topic and that have the required background.

By 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.

By Pablo G G

Sep 10, 2020

Nice intuitions of what to do when you need to improve model, and believe me, you will! :D If you set up your local jupyter lab and start playing with deep learning, you will quickly see that this course is gold in order to optimize you DL algorithms!(its all about getting that loss to 0.0000001! :P) Don't understimate this teachings!

By 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.

By 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.

By 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.

By Kunjin C

Sep 05, 2017

Compared with the previous two courses in this special, this course is more practical and useful when we are actually trying to solve real-world problems. After taking this course, one will have a clearer mind in terms of making the most out of data from different sources as well as coming up with better solutions to certain problems.

By Cristina N

Dec 19, 2017

Absolutely LOVED this course: with the two "case study" you can really get a sense of what does it mean to set up a real ML/DL project and how to address the problems you may (and you're very likely to) face by building up or leading a ML/DL project.

If you're thinking about learning Deep Learning, this course is absolutely NECESSARY!

By Tesfagabir M

Aug 18, 2017

This is my third course in the deep learning specialization. I have learned a lot related to different strategies with machine learning projects. The concepts are easily explained with practical examples. The assignments are also very helpful for applying in real machine learning projects. Thank you professor Ng. You are the best!!!!

By pedro o

Aug 16, 2020

This is a great course for anyone new to machine learning. It focuses on the core challenges one may face while carrying out machine learning projects. Overall, it is a must take for people new to the field,professionals,hobbyists,etc .Thank you Andrew Ng for being a great instructor, I look forward to completing the specialization.

By Ayomi A

Mar 01, 2018

Excellent course and very interesting !!

Allows you to analyze real ML problems and supports you with the basic and essential skills needed to develop ML algorithm and evaluate its performance and how to approach the issues that one can encounter during the iterative process, what are the options, which is the best to go with, etc.

By Ayush P

Dec 03, 2017

Really good course to develop an approach to NN problems. I thank you Sir Andrew Ng for all the courses that you have made available on Coursera. It has been an really awesome experience learning about neural networks from you. I will finish the remaining courses and recommend it to people who want to pursue a career in ML and AI.

By Jingxiao Z

May 21, 2019

This is a practical course, extremely helpful for those who have met so many troubles in realworld projects. It is quite helpful for startups, where we can implement those ideas immediately. On the other hand, the transfer learning and end-to-end learning paradigms might be very useful but challeging in big companies and sectors.

By Nouroz R A

Sep 28, 2017

This is one amazing course because it exposes you to a 'real' ML/DL problem. As a newbie I learned a lot and hope that in future I will once again do it as a ML research/development Engineering Manager. This is something very practical and now while doing big projects I will consider the learning of this course. Thanks Andrew Ng.

By Mohab S A

Jul 18, 2020

Exceptional, one of a kind strategic course for ML practitioners. The amount of wisdom and knowledge shared in this concise course would definitely save any budding ML engineers from the common pitfalls that many teams may still face. It also sets the foundation stone for cultivating prospective machine learning project leaders.