Chevron Left
Advanced Machine Learning and Signal Processing(으)로 돌아가기

IBM의 Advanced Machine Learning and Signal Processing 학습자 리뷰 및 피드백

4.5
618개의 평가
94개의 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 ibm.biz/badging....

최상위 리뷰

A

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.

PS

Nov 16, 2019

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!!!!!

필터링 기준:

Advanced Machine Learning and Signal Processing의 93개 리뷰 중 51~75

교육 기관: Ankit M

Dec 17, 2019

Good

교육 기관: N B

Nov 05, 2019

nice

교육 기관: Alexander B

Nov 07, 2019

Overall a decent course. The lecturers could go into more depth with some of the topics they covered to allow the learners to really grasp the concepts. I felt all of the assignments were too simple, possibly allowing you to pass even if you don't completely understand the material. More depth in the lectures and challenging assignments would leave me completely satisfied.

교육 기관: Euripedes B d C N

May 20, 2019

O Curso é ótimo e apresenta muitos conceitos de Machine Learning e Processamento de sinais, mas faço uma ressalva, pois como o próprio nome diz é Avançado e o candidato precisa ter uma boa base de programação, particularmente precisei pesquisar bastante sobre Apache Spark e Systemml pois minha formação não é de TI.

교육 기관: Albert S

Jan 16, 2020

Assignments were a bit too easy. I didn't really have to understand 90% of the lectures to complete the assignment. Most changes were related to spark.sql knowledge and how to instantiate classifiers and such.

교육 기관: David A

Feb 17, 2020

Overall good course; very interesting concepts given in the lectures. I only wish the programming assignments were a little more interactive and deeper than "fill in the blank." Great stuff though thank you!

교육 기관: Amy P

Sep 07, 2019

Very interesting concepts and more math than other courses, which was nice. The audio quality of guest lecturers needs to be improved, but I appreciated the video content and hands-on examples.

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: 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: 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: 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: 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: 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: Sameera P

Sep 16, 2018

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

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: Jeffrey G D

Jan 15, 2020

Great concepts, but light on application.

교육 기관: BAUDRY S

Nov 23, 2019

Some spelling errors here and there

교육 기관: Rich E

Feb 25, 2020

Great explanations and examples

교육 기관: 俊鴻 林

Dec 03, 2019

Thank courser and teachers

교육 기관: Aditya S K

Jun 27, 2019

Great learning!!!

교육 기관: Filip G

Sep 27, 2019

This course is second in the IBM specialization. It covers basic supervised and unsupervised ML models on a very high level with too little explanations. Especially around veryfing results and optimizing models. Metrics, crossvalidation and gridsearch are all explained on cca. 10 minutes! On top I can't figure out why did the authors put in a whole week on Fourier Transformation.. :S

교육 기관: Stefan T

Dec 31, 2019

I don't like giving negative reviews, but for the amount of money asked for the certification I would expect better quality of material (audio especially). I took many courses back in the day it was free to do and the quality of material was much much higher.

The course is well presented, but if you don't use IBM environment and their libraries, you will not be so happy to follow.