Вернуться к Advanced Machine Learning and Signal Processing

4.5

звезд

Оценки: 570

•

Рецензии: 87

>>> 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....

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.

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!!!!!

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автор: Seylan N

•Feb 13, 2019

I feel bad giving it such a low rating, but I have to be honest. I did not learn much from this course. There was nothing "advanced" about the machine learning, and image processing was only gone over in the final week, and it was mostly just an overview of the important topics/concepts. This course lacked the rigour and depth I was expecting. Maybe my expectations were too high. The assignments given were very simple. There should have been more interesting projects/assignments. The quality of the lecture videos was mediocre, in terms of both presentation and content. Someone can finish this course within a week, in fact just a few days, without even putting much effort into it. Overall this course lacked a coherent structure and it felt like it was put together in haste without much consideration for students.

автор: Jozeene

•Jan 01, 2019

Such great material. I really loved working out the notebooks. I have to go back and redo the IoT starter exercise to get better accuracy, but this was awesome!

автор: Amardeep S

•Feb 15, 2019

In general the course is excellent. However, it had a lot of information contained for a 4 week period especially week 2. I definitely learned a lot.

автор: varshaneya v

•Jan 03, 2019

Programming assignments were not challenging. Good course coverage.

автор: Edoardo B

•Aug 22, 2018

I like very much the architecture-based approach of these courses/ specialization.

At the end, the goal of an Enterprise, in a general sense, is to satisfy the local or global community necessity in an effective and efficient way. Surreally with the choose of the correct technology, frameworks, languages, instructions, details.... but , at the end, what is really important is the value offered.

That said, I think, that this specialization, provides the mindset, the knowledge, the skills and tools applicable in a corporate environment. Technology is important, yes, but, from my point of view, it is most important to consider the value that is emerging from the holistic approach of all the topics in the different modules of the courses, including also the final capstone project.

Thank you very much Romeo and all instructors for this continuous learning professional opportunity

автор: Dmitry B

•Jan 11, 2019

This course introduces some of the most popular methods of supervised and unsupervised machine learning. While it doesn't go deep into details behind the intuition, it gives a good explanation of when and why these algorithms can be applied.

автор: Shakti s

•Jan 05, 2019

I would like to recommend this course this is really interesting and most interesting part is the signal processing which builds an proper understanding of the math buzzwords like fourier and wavelet transform.

5 stars to the course

автор: Akosu 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.

автор: Jan K

•Dec 15, 2019

Great course for beginners who want become advanced users in signal processing and machine learning. Thanks a lot for great examples and letting me know what I should learn in next steps.

автор: Paulo R R

•Feb 25, 2019

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!!!

автор: Prithvi S

•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!!!!!

автор: Ravi K

•Jan 13, 2019

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

автор: Sukh S S

•Aug 22, 2019

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

автор: Paul B

•Mar 13, 2019

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

автор: Daniel T

•Apr 29, 2019

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.

автор: Eleni K

•Nov 02, 2019

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

автор: Ilario M

•Jun 26, 2018

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

автор: Jorge A V

•Jan 28, 2019

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

автор: Sven

•Oct 05, 2018

Very good data science specialization covering many interesting advanced technologies!

автор: Azeezur R

•Oct 23, 2018

Very good course for learning, Fourier transformation explanation was the best one

автор: Ted H

•Aug 21, 2019

The Signal Processing was eye-opening as a way to extract data from sampled data.

автор: Oghenekaro J O

•Aug 07, 2019

Great Course. You'll learn a lot about the mathematics of some key algorithms.

автор: Khawar A A

•Jan 27, 2019

Great course. superb instructor Sir Romeo. !! I am big fan of him now. !!

автор: Michael S

•Jul 19, 2019

thanks a lot to my motivated, sympathic and well prepared teachers

автор: Giovani F M

•Jan 02, 2020

Great course.

I really enjoyed the approach about FFT and Wavelet.

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