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Advanced Machine Learning and Signal Processing に戻る

IBM による Advanced Machine Learning and Signal Processing の受講者のレビューおよびフィードバック



>>> By enrolling in this course you agree to the End User License Agreement as set out in the FAQ. Once enrolled you can access the license in the Resources area <<< This course, Advanced Machine Learning and Signal Processing, is part of the IBM Advanced Data Science Specialization which IBM is currently creating and gives you easy access to the invaluable insights into Supervised and Unsupervised Machine Learning Models used by experts in many field relevant disciplines. We’ll learn about the fundamentals of Linear Algebra to understand how machine learning modes work. Then we introduce the most popular Machine Learning Frameworks for python Scikit-Learn and SparkML. SparkML is making up the greatest portion of this course since scalability is key to address performance bottlenecks. We learn how to tune the models in parallel by evaluating hundreds of different parameter-combinations in parallel. We’ll continuously use a real-life example from IoT (Internet of Things), for exemplifying the different algorithms. For passing the course you are even required to create your own vibration sensor data using the accelerometer sensors in your smartphone. So you are actually working on a self-created, real dataset throughout the course. If you choose to take this course and earn the Coursera course certificate, you will also earn an IBM digital badge. To find out more about IBM digital badges follow the link



I learned a bit in terms of signal processing and the theory behind that. That could have been a course by itself, but the addition of great machine learning material made it a wonderful experience.


A career changer course, thanks the hand-ons which is second to none, i have gained experience which on other online course can produce, thanks to IBM for this course which timely and excellent.


Advanced Machine Learning and Signal Processing: 26 - 50 / 204 レビュー

by Paulo R R


Excelente curso, com ótimas explicações, bem detalhadas e sem rodeios. Os exemplos são práticos e abrangentes! Parabéns à equipe do Coursera e à IBM pelo excelente curso! Nota 1000!!!

by Jeevan P


The information obtained through this course was excellent.Enjoyed learning through this course. Thanking both the professors for making this course an enjoyable learning experience.

by Prithvi S


Great course. Finally after learning Transformation methods like Fourier and Wavelet, I finally got to learn real life problem solving capabilities of them. Learned a lot!!!!!

by Emmanuel A B G


For people with some background in signal processing, the explanations given here are very appreciated, specially the simple way that Wavelets were explained.

by Khaled A


I loved it, it met my expectations, I read that this course was difficult for many but I think the level is decent. I don't know maybe you have simplified it

by Ravi K


Excellent Material. The lectures and assignments are very good. Lectures sometimes felt a bit theoretical but needed that to understand concepts well.

by sukh s


The explanation of some of the black box tools like PCA, Covariance, and Fourier Transformation is amazing and very clear and easy to understand.

by Paul B


The PCA/FT/FFT material is awesome. The presentation is great. The assignments while not great, where a sufficient taste of watson studio.

by N.Srinivas


Amazing course! I thoroughly enjoyed detailed explanation behind Naive Bayes and PCA. Digital signal processing is like the cheery on top!



A really good course on advanced topics of machine learning and signal processing with an in-depth explanation of each topic very clearly.

by Alfredo P


Excellent material and Instructors. It would be great f we could get the instructor's sample notebooks that they used in their lectures



Fantastic ! (just a little recommendation: before enrolling, it is recommended that you have a respectful Machine learning background

by Daniel T


This was a nice review of my undergraduate work at Northwestern, except that we didn't have Spark back in the day. Very cool course.

by Njoku, U F


I loved that the mathematical concepts behind the various techniques like Bayes theorem or Fourier transforms were well explained.

by Robert F


It's pretty advanced in content. Someone with a background in math would love it. I would like to learn Apache System ML coding!

by Edward J


Thank you so much Romeo and Nikolay. Your explanations were so clear and I feel inspired - I could listen to you both all day!

by Farrukh N A


Excellent! Advances course mathematical and statistical cover along with programming in python (Apache Spark and System ML)

by Kshitij T


Whole course was to exciting and knowledge full that it bind me to go on and on until I did not gained the whole knowledge.

by Jan B


It was a really nice course to learn the way to implement the most used ML algorithms with an easily scalable method

by Eleni K


Quite different from the previous course! Much better, with more thorough explanations and hands on experience.

by Ilario M


Very well structured, easy to follow/understand. This is a hot topic at the moment and helped me in my job.

by Ricardo S


Gives an in-depth overview of the main approaches/methods in ML and Signal Processing. Very well designed.

by Gouri S C


The course was nicely designed. Really enjoyed and learnt a lot. I especially thanks to the instructor.

by Axel A J A


Excelente curso, e información muy concreta, aunque los ejercicios de programación se me dificultaron

by Jorge A V


Interesting that they add signal processiong and IoT. Something usually overlooked in other courses