I felt that I took the best descition in taking this course, because the professors took this course with atmost clarity and made even the difficult concepts understand easily.\n\nThank you Professors
Thanks Coursera and Duke University for this course. It is very insightful to get understood the basics of ML and applied ML in numerous fields. It really made me to move ahead with ML domain.
교육 기관: SHIVAKUMAR S R•
교육 기관: Katha P R•
교육 기관: Dr. S C•
교육 기관: Sayan G•
교육 기관: Sean C•
Labs are great hands-on training, but the lectures and lab texts don't sufficiently prepare the student for the assignments. Watching them and reading the text will not give the student the skills to solve the assignments, forcing the student to search online for a better tutorial. I recommend providing the complete code to create a MLP, CNN, SWEM, RNN, LSTM and GRU.
With a basic template created, the lab questions can then have the student change epochs, batch sizes, etc.
I am aware that some basic templates were provided, but providing a SWEM and having the student convert it to a RNN is a huge jump. I took detailed notes during lectures and read the lab notes, but ultimately had to find other resources to complete the assignments, because the answers were not provided by this course.
I hope this critique does not come across as a personal attack. I teach electrical engineering and understand how difficult it can be to fully explain complex topics. Thank you, all four of you, for creating this course!
교육 기관: Dziem N•
I would like to thank Prof. Carin for a very lucid and intuitive explanation of the major concepts in Machine Learning covered in this class. This is the best explanation of the concepts of CNN and Reinforcement Learning that I have found so far !!!
I am also a little bit disappointed by the set of Programming Exercises at the end of some the lectures by other teachers. I think instead of giving students examples of programming using raw, low-level TensorFlow APIs because it overwhelms the main concepts. It is better to use high-level back end tool like Keras (NOT Slim !!!)
교육 기관: Chen S•
It is a very basic introductory course to important fields in machine learning. It tells important models like CNN and RNN and LSTM. but it does not go deeper into the technical levels of these models. Some parts about mathematics are not very satisfying. Also I feel like the course doesn't provide enough training for the coding work. Nonetheless, it is a good course to start with machine learning and the instructors repeat the concepts from the previous class, which helps me a lot in understanding the concepts.
교육 기관: Carlos C•
Good course and practical samples with good depth and looking beyond the implementation of tools, especially regarding the structure of algorithms and complex mathematical concepts behind the functions and parameters in Machine learning models. Thanks professors!
교육 기관: Fevzi E B•
This course was good as an introduction course, appropriate analogy is used for facilitating. However, when it comes to assignments, there should have been videos instead of documents for better understanding and answers could be shown afterwards.
교육 기관: Phijit D B•
It was very good. I understand the most of the part what the professors told and was able to learn about what is actually a deep learning is and why machine learning is needed. Hop it help many students through this videos.
교육 기관: Arpita C•
I would recommend this course to someone who wants to gain basic insight into the world of Machine Learning. The course is organized in a way that should be easier to follow by the ones enthusiastic about Machine Learning.
교육 기관: Franco B•
Course provides the fundamental of machine learning techniques, representing the state of the art of image and text processing; some more examples could help in enforce the meaning and intermediate results in applying
교육 기관: Akash K•
Great course for the comprehensive understanding of Machine Learning and consequently various new models like Deep Learning and CNN. This is highly recommended to have a good start in the field of Machine Learning.
교육 기관: Vishal G•
Nice experience to this course to get introduced about machine learning. It really help to those who want to start his career in this field.
교육 기관: Erb F L•
The course is very well presented and structured. I think it could be better if it has more examples in tensorflow (specially in week 4).
교육 기관: MAHA Z K•
The course was very engaging, i learned a lot from scratch, and i like the quizzes in between the lectures. Helped me stay on track
교육 기관: Dhawa S D•
This was the exact course I was looking for last six months. I would like to thanks all the instructors for this amazing course.
교육 기관: Manish G•
Very good beginners course. Topic is explained mostly in simpler way. The sequence and sync of topic can be improved.
교육 기관: AKSHAY P•
Content was really knowledgeful and instructors gave the in depth gist of Machine learning and deep learning
교육 기관: Neeraj S•
Amazing experience.I've got to know basics of machine learning that how models are studied and implemented.
교육 기관: SAMBARAN M•
It was indeed helpful for students who want to know about this field in a introductory phase of learning.
교육 기관: Juan R•
It would be great to have more small practical exercises as it always reinforces the theory explained
교육 기관: Darshan G•
Very good theory. But I feel that more hands on work is required to understand the concepts better.
교육 기관: BASAPURAM P•
I learned lot of things in this course.it will help me to do other courses,it improves my skills
교육 기관: f M A w•
thanks teachers that should expreianced in this course so all thnks the coursera team