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Advanced Machine Learning and Signal Processing(으)로 돌아가기

IBM의 Advanced Machine Learning and Signal Processing 학습자 리뷰 및 피드백

999개의 평가
169개의 리뷰

강좌 소개

>>> 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

최상위 리뷰


Sep 08, 2018

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.


May 14, 2020

Good one! I liked the wavelet transform part. It was nice to visualize everything. However coding assignments are easy, almost all the codes are written, please insert some more coding part.

필터링 기준:

Advanced Machine Learning and Signal Processing의 168개 리뷰 중 101~125

교육 기관: yash k

Oct 21, 2019

Amazing course with real life usecase. A bit more explaination would have helped as most of the content is based on the fact that the viewers are familiar with SparkML/ SystemML

교육 기관: VISMIT C

May 11, 2020

Really good if you know a bit about Machine learning, it's not important to know this in DML, could focus on this in python with scikit but still thoery is very useful

교육 기관: Alaso L K

Apr 01, 2020

Definitely worth the time, with good practical examples and a ton of maths behind Fourier Transform analysis and applying machine learning pipelines to Apache Spark.

교육 기관: VIGNESH K K

Jul 23, 2020

romeo class was too good , his information are too short and catchy , i like this course due to him , i am eager for any other course which he would teach

교육 기관: Zexi Z

Jan 01, 2019

fairly good. not perfectly organized but a little bit relax. good pace for workshop style training for some parts and enough details for some other parts.

교육 기관: Eugene N

May 16, 2020

This was a good course but I don't know how signal processing will be useful for some people who aren't in the field of physics (signal processing)

교육 기관: harsh j

May 28, 2020

This course help me learn many new concepts but I would suggest some coding exercises in the course would much better for the better learning.

교육 기관: Michael B

Jul 30, 2019

Great course overall! Personally, however, I didn't think the digital signal processing portion was as useful as the first three weeks.

교육 기관: MEZOUAR b n e

Jun 04, 2020

it was very interesting to attend this course ,it had both theory and practice parts and all what you need to use in the future

교육 기관: Ceren A

Apr 11, 2020

Great classes from Nikolai but not so much from Romeo! Huge difference in levels, presentation, learnings between the 2.

교육 기관: Petch C

Dec 27, 2019

Content of the course is good and easy to understand but I would be better to add more activity to the assignment.

교육 기관: Anh-Quang N

Jun 07, 2020

It is an OK course to learn the basics of ML in and how to use the IBM infrastructure with SparkML for ML

교육 기관: Andrés

Feb 17, 2019

The theory is good but the excercies could be more complete and big to cover all the points in the theory

교육 기관: Sauraj C

Nov 26, 2019

4 Star because course is not based on project it's good to learn the theory project is important

교육 기관: Fasakin O A

May 20, 2020

The course contents are great but there is no much practical details about fourier transform.

교육 기관: Srivatsan R

Sep 01, 2019

Great Online Course. Videos involving IBM Watson studio can be explained in a better way.

교육 기관: Chan H Y

Oct 03, 2018

This course covers many traditional approaches to machine learning and signal processing.

교육 기관: Vignesh K

Jun 27, 2020

A very intuitive way of learning and great to see a mixture of ML and Signal Processing

교육 기관: Sameera P

Sep 16, 2018

I like what's taught in the course but the questions assignments are too simple.

교육 기관: Ahin B

Jun 15, 2020

I have earned good knowledge on Machine learning along with python programming.

교육 기관: Kuldeep S S

May 06, 2020

This Course is very good but programming explaination is not good.

교육 기관: John M

Jan 14, 2019

Great course overall. A few small wrinkles that need fixing.

교육 기관: Pratyush A

Oct 18, 2019

IBM Watson studio can be made more user friendly.

교육 기관: Swarupa D

May 22, 2020

it's very helpful...Thank u Sir for guiding me

교육 기관: Krishna K N

Apr 14, 2020

Programming exercises could be more difficult.