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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
1,156개의 평가
209개의 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

MM
2020년 4월 28일

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
2018년 9월 7일

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.

필터링 기준:

Advanced Machine Learning and Signal Processing의 207개 리뷰 중 101~125

교육 기관: SOUMYAJIT D

2020년 10월 1일

Very good , awesome

교육 기관: Marvin L

2020년 4월 10일

it was educational

교육 기관: Mukul K M

2020년 6월 13일

excellent course

교육 기관: Madan T

2019년 12월 10일

Excellent course

교육 기관: Saman S

2019년 10월 26일

that's wonderful

교육 기관: Dr P R K

2019년 10월 18일

very informative

교육 기관: Yuliia H

2021년 6월 18일

G​reat course!

교육 기관: Alexander L

2021년 5월 8일

Very cool job!

교육 기관: CARLOS S

2019년 12월 25일

Great course!

교육 기관: Suhas J

2020년 9월 20일

great course

교육 기관: Warren P

2020년 5월 9일

Great class!

교육 기관: Hadhrami A G

2020년 5월 6일

Very Good

교육 기관: JAYDIPKUMAR U

2020년 6월 22일

too good

교육 기관: Jeff D

2021년 1월 24일

Thanks

교육 기관: Jérémie B

2020년 2월 3일

Good.

교육 기관: Bikash R

2019년 11월 21일

Great

교육 기관: Ankit M

2019년 12월 16일

Good

교육 기관: Nyam-Ochir B

2019년 11월 5일

nice

교육 기관: Avijit P

2020년 7월 8일

The difficulty level of the course is as it states, intermediate.

Both the instructors are quite good at explaining things and also provide a little insight as to why they're choosing to do something at any given moment.

There is this one lecture though from a guest faculty that just plain reads out what's written in the presentation slides.

Although they try to explain every short thing, it might go over one's head or require repetition if the reader is 2 or 3 viewings with the mathematical concepts behind the algorithms previously. But the course still felt pretty self-contained to me,

Still, it's an overall balanced course that can't be completed unless one understands what the code is doing. Great for getting insights on and developing data science intuition.

교육 기관: Humberto D

2021년 6월 21일

T​he instructors of this course are very good about explaining the intuition and the code. However, I must admit that the treatment of the mathematical content was superficial; there was not enough time devoted to mathematical formulations of the problems and their solutions. In fact, it is such that one should already be familiar with the mathematics of data science in order to understand what goes on under the hood during the coding implementations. Otherwise, one does not get a sense for why the techniques that are used work the way they do.

교육 기관: Scott B

2020년 5월 4일

The information in the videos is excellent. I am actually very please by how succinct and clear the topics had been covered. My reason for giving 4 stars is because the programming assignments do not really help crystallize the new material. They may include a fraction of the concepts that are covered. It would be nice if the assignments involve stuff like the inclusion of param grids, comparing different ML algorithms, implementing PCA, etc. Also would be nice if there had been a review of the Fourier Transform material using SparkML.

교육 기관: Alexander B

2019년 11월 7일

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: Taresh B

2020년 7월 5일

I like the course but I feel that it really needs more depth. It feels like most topics have been just skimmed through and not explained very well. The IBM tag is something that attracts you but if you wanna delve into the details, this course will tell you what to learn, and then you'll have to go on youtube and look for resources.

교육 기관: Rishiraj A

2020년 7월 8일

I liked the course.

I like Week 4 of Advanced ML course. It is very fulfilling.

But, I think the portion of large data handling using parquet and spark is still missing in both the course (Scalable DS and Advance ML). There should be a session where is taught how to create parquet files and how to store them in object storage.

교육 기관: Euripedes B d C N

2019년 5월 19일

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.