YG
2022年8月8日
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 ...
RG
2022年8月3日
Awesome specialisation. Allowed me as a beginner to get a good initial understanding of machine learning and put begin to put concepts into practice.
by Yuriy G
•2022年8月9日
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 ...
by Richard G
•2022年8月4日
Awesome specialisation. Allowed me as a beginner to get a good initial understanding of machine learning and put begin to put concepts into practice.
by Eduardo A
•2022年7月29日
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 ->
by Diego C M
•2022年7月29日
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!
by James P
•2022年8月1日
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).
by Austin S
•2022年8月5日
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.
by AustinQi
•2022年7月31日
A sincere thanks to Andrew and all Deep learning AI crew, you guys/gals are the light of machine learning community.
I have a kid of 3, cant wait to introduce all your guys hard work to him someday in the future. Maybe (hopefully not) he is not interested in these topics, but the thing I want him to know is " how to define good people", my answer is "they share and care".
by Baiwei Z
•2022年8月12日
Andrew is an excellent instructor who can break down complicated concepts into pieces that are much easier to understand. I enrolled both Machine Learning course (the old version) and Machine Learning specialization (latest version) and found both of them entertaining and informative. Hopefully I will learn more about AI from courses provided by Andrew in the future!
by Serban G
•2022年8月11日
Excellent videos and labs, clear explanations of technical details with emphasis on developing an intuition while learning the technical concepts. I enjoyed it and appreciated the use of current machine learning software frameworks in the videos and the labs.
by Brooks J
•2022年8月7日
Not only did I get a tremendourse from this course, I'm thinking about how to reinfoce my own learning, with the tradeoffs that suggests between immediacty and payoff, as well as introduce a touch of randomness.
by Bruno R S
•2022年7月30日
Very few courses explore the insides of Unsupervised Learning and Reinforcement learning like this one.
by Ashraf H
•2022年8月9日
Outstanding course and specialization. Thank you!
by Jeremy L
•2022年8月6日
Amazing course!
I learned a lot!
by Jan S
•2022年8月8日
Best out there!
by 周良骥
•2022年8月8日
Great course!
by Raghavendra N
•2022年8月2日
Great course on understanding key machine learning techniques without getting too deep into the mathematics.