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Advanced Machine Learning and Signal Processing(으)로 돌아가기

IBM의 Advanced Machine Learning and Signal Processing 학습자 리뷰 및 피드백

4.5
별점
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 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

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 126~150

교육 기관: Pragati A

Jun 28, 2020

Both of the instructors were really amazing.

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.

교육 기관: Jeramie G

Sep 04, 2019

The information and examples presented in this course are helpful and pretty easy to follow. My only complaint is - and this is true for a lot of these online courses - the programming assignments are way too easy.

I know this isn't a full-blown college level curriculum. I feel like I retain the material better when the assignments are more challenging.

교육 기관: Roger S P M

Jan 30, 2019

This is the second in the Advanced certificate series. By this time you are starting to understand their teaching method. So it is a better experience than the first one. Also you are getting more experience with the studio, cloudant, and Node-RED - which is very helpful and rewarding.

교육 기관: Björn ' H

Sep 19, 2019

The assignments are too easy, the level of coding required is not very challenging, it's just a fill-in-the blanks exercise, I don't know if I could actually do any of these things on my own with a new data set.

교육 기관: Greg R

May 12, 2020

Overall very useful material covered however I was disappointed that some key concepts such as Baynesian inference and PCA were not well explained. I supplemented most of that material from Youtube.

교육 기관: Mario E R T

Aug 09, 2019

The learner needs to do more by his own. I think the course should follow up on the teaching style from the IBM specialization of Data Science. The teachers are good at replies.

교육 기관: Borvorntat N

Jul 08, 2020

Assignments are too easy, and not cover every lecture that I have learned for advanced ML, also some of the lectures are quite short.

교육 기관: Anastasiia S

Sep 15, 2019

Not enough programming assignments and the ones in this course are too easy for the "advanced" course

교육 기관: Salvatore S

Jan 12, 2020

The assignments are way too easy. Not very challenging for a course with 'advanced' in its title.

교육 기관: Thiago d S B

Jul 07, 2020

Some videos with low quality so it was hard to read the code and lack of pratical exercicies

교육 기관: Ayushman S

Jul 18, 2020

The course might need some updating, it does give a lot of information about many things.

교육 기관: Riku S

Feb 07, 2019

A tad too much IoT for my professional interests (was part of larger "Specialization")

교육 기관: Nima

Jun 08, 2020

Some explanations were good but that was not enough for covering machine learning

교육 기관: Mark B

Apr 17, 2020

Hard to follow at times... found a lot of assistance in discussion forum

교육 기관: Prashant B

Aug 29, 2019

The spark usage is very limited. Assignments could be more challenging.

교육 기관: Nicolas M

Apr 18, 2020

It should be useful to introduce more practical exercises

교육 기관: Markus W

Sep 24, 2019

well explained, programming assignments are worthless.

교육 기관: Santiago M L

Jun 28, 2020

It's a little bit comlicated develop the activitites