The best thing this course did for me was to remove the enigma of machine learning. This specialization is not so much about going deep into individual machine-learning algorithms and techniques as it is about exposing a student to the broad spectrum of all the different kinds of problems for which machines can be programmed to learn a solution. Once a student completes this course, they have a very good idea of the kinds of problems that can be solved by letting machines learn how to solve those problems and specific algorithms/techniques that need to be used for that particular kind of problem. A student can then research additional resources for the specific problem they have at their hand and take a deep dive into developing a working solution for their specific problem. This course enables you to start that journey by taking away the fear created by the belief that machine learning is something very challenging.

It simply exceeded my expectations. I recommend it to whoever who is trying to learn the concepts and need tips related to industry practices, and overall wants an applied approach.

This course is an excellent course for introductory machine learning. All of the topics are covered in great detail and It is an honor to be taught by Andrew N.G, the Great teacher.

Great course and very well taught by Andrew! The only problem is that now I am left with a burning desire to learn even more and start applying all this knowledge everywhere ...

Awesome specialisation. Allowed me as a beginner to get a good initial understanding of machine learning and put begin to put concepts into practice.

Excellent Intro to ML topics, I'm grateful to have taken this course and the explaning way for dummies of Andrew Ng. Towards ML Engineer ->

The video explanations are amazing, but the practical exercises are just frustrating. The difficulty is fine, could be more challenging actually and also require you to do more than what was explained in the videos. The annoying part are the unit tests. I almost always get a fail even though my functions return the expected output. I have compared my function to the solution and I always get the same results. I do not know how the unit tests are designed but they do not fulfill their purpose. It is frustrating that I have to write functions in a pre-dedfined way to get a pass even though my function generates exactly the same output. Even more frustrating that the explanatiosn in the notebooks do not explain why the function has to be written exactly in that way, when a more efficient way with less or even no for loops is possible. I would recommend to rather play around and write your own classes on your local machine and compare output to scikit-learn algorithms. I think you learn more that way than having to resort to copy pasting code to get a pass on the unit tests....

week 2 and 3 left me with a feeling of a very partial understanding of the material

Good general introduction but superfacial, and with too many small errors in the video contents.

The first course felt a bit easy, and I only gave it four stars. However, after finishing the second and third courses, I now understand why the hints in the labs were included and it saved me a lot of time debugging. Sometimes your answer might be the same as what is expected, but the shape or dtype might be different.

Sure, you can just copy paste the answers from the hints, but that's your loss. Same goes for the quizzes, that actually do get a bit more challenging in courses 2 & 3.

The only thing I would have liked to see would be some optional math questions, but even without those this entire specialization is hands down the best one I've taken on Coursera along with PY4E.

This specialization is definitely worth your time, and I recommend watching the CS229 lectures on youtube as you're going through it if you're looking for a bit more of a challenge!

Fully recommended course, another masterclass on ML from Andrew Ng and his team! I was able to quickly build a decent foundation on UL while enjoying the content and exercises. As in the other spezialization courses, each topic starts with the algorithm intuition before jumping into the specific math and nuances. The jupyter notebooks are excellent, I found them super effective to understand the practical implementations of K-means clustering for image compression, Gaussian distributions for anomaly detection, collaborative (and content) filtering for movie recommendations, and reinforcement learning for a virtual lunar lander 🤖 Many Thanks!

Prof Ng is a fantastic teacher! The three courses are really well structured and builds upon themselves. I expected to learn some cool things, and I sure did - some mind-blowing machine learning things! The mentors on the forum are really helpful and respond to questions will thoughtful replies, which is great.

Prof Ng is passionate about machine learning, but is also sincere & humble, and is also very mindful of the ethics of AI and how it impacts people. The course is pretty cheap, and I can tell Prof Ng really wants to pass on AI knowledge.

I'm full of admiration for Prof Ng, who is a really nice person!

One of the best courses I joined at Coursera (including ML specialization courses 1 & 2 from Andrew). Very well organized and structured, appropriate learning rate with lots of recaps in particular for me as a newbie, strong focus on teaching the ML techniques and not on coding. It's a lot of stuff all together but the slides are a good handbook for later daily work. The only thing I missed a bit is an 'executive summary' of each week and course, resp., with the most important take-aways in one single slide. But that's just a tiny little thing. Thanks, Andrew and team for this really excellent course!

Thanks Andrew Ng and Team!!

the courses are beautifully explained, and the lab are greatly prepared and organized!

I have wanted to follow this course for a long time, and I am very grateful that finally, I had some time to make it!!!

Special message to Andrew Ng: you make this course very special and exceptional! Indeed, your compassion and concerns to make the world a better place are refreshing in today universe. You really make the world better by sharing knowledge in a great way. I wish you all the best in your multiple endeavors :-)

Fabrice

This is one of the best courses in Machine Learning for topics on Unsupervised Learning and Reinforcement Learning. Andrew NG is one of the best teachers who can make many complex topics more easy to comprehend and at the same time make sure the technical side of things is also delivered. I would recommend this course to anyone who has completed the previous 2 courses in the specialization. The practical examples covered and the help from DeepLearning community is very valuable. Have a great learning experience. Thank You.

Amazing assortment of videos. Just one STRONG suggestion. the last graded lab in week three, based on reinforcement learning has a shortcomming that it uses graph tensors. this really messes up the code and makes it hard to use. Infact i myself dedicated three hours to debugging it to realise, that the tensors used in the code are modified and cannot be converted to numpy arrays. This made it impossible to code for it. please look into this matter. Thankyou

The best ML course ever made, especially course 1 and course 2. Super helpful not just tell you how to use the model but also walk you through all the details and logic behind each model. Thank you Andrew! I didn't try hard in my college time and missed the chance to attend Stanford grad school, but it is great being a virtual student of yours. I wish you and your team all the best, and it is so blessed for us to have you in ML industry!

Thanks a lot to the entire course team. This course along with all the 3 courses machine learning specialization was a great introduction to Machine Learning. Admired the perfect pace at which the training was delivered and thanks for all the practice lab and quiz sessions. Learnt also the way to train,present the content and neatly and duly acknowledge the efforts of the contributors and the learner . Great course and team. Thank you!

Great introduction to three difficult topics. Overall the specialization quizzes/assignments have been a light touch. The unsupervised and recommender weeks were a little tougher while reinforcement learning was definitely a friendly introduction with a fun assignment. Great instruction and clearly a lot of time invested into making interesting assignments (very much appreciate the change to python from octave).

Big name on this course! While you will be further impressed only you learned from details and reload some detail steps. I strongly recommend people to learn even you're just a commercial people in data, tech companies. For data analysis is very great but must to have 101 machine learning course which are not only incl. tech and ML but also integrated biz sense in many case studies and sharing during the courses.

Very good course for a strong foundational understanding of machine learning. I feel very greatful that courses like this are even available for people like me and I will definitely continue to take other courses provided by Andrew. A very comfortable and friendly person who also provides explanations in a way that makes me understand concepts I didn't think I would be able to understand.

This was an amazing first course to take. I was originally taking the original Machine Learning course when this came out. I switched and it was a very welcome change. Using Tensorflow and Python instead of Octave/Matlab was nice and getting to learn from all the advances was really cool. The interactive notebooks made learning really fun and much easier to get my hands on the material.

This course (along with the other two in the Machine Learning specialization series) is the best course to learn about Machine Learning topics like unsupervised learning, recommenders and reinforcement learning and #BreakIntoAI. Sir Andrew Ng is the best ML teacher ever and I thank him and his team for having provided me with such a great opportunity to learn. Thank You !!!!

In this beginner friendly course, Andrew taught the basic Machine Learning learning concepts in an easier to follow manner. The videos cover Mathematical intuition behind many of the basic machine learning algorithm, while the practice labs helps you to implement them. Thanks to Andrew and rest of the team for this amazing introductory course to Machine learning. Thank You...

I would like to thank all the members of Coursera for designing this course, especially Dr. Andrew Ng for teaching such complex stuff with much clarity and with fun-based activities (videos and labs). I really like the tools you used for the demonstration purpose (e.g. the toys of your daughter :))

I hope to make the best use of this learning.

Thank You once again.

D_Kaur