Вернуться к Advanced Machine Learning and Signal Processing

4.5

звезд

Оценки: 997

•

Рецензии: 169

>>> 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.

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.

Фильтр по:

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: AKASH M

•Apr 09, 2020

Very well structured course and very intuitive. Was able to uderstand every concept with amazing depth and loved it. I wish my uni teachers used this style of teaching.

автор: varshaneya v

•Jan 03, 2019

Programming assignments were not challenging. Good course coverage.

автор: Mohamed A M

•May 19, 2020

I was able to learn spark and how to use it in machine learning with different datasets and go deep in machine learning and signal processing, which wil lendose my background in the last field

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: Osvaldo G A

•Jun 17, 2020

The course is great if you come with the right expectations for it. Let me elaborate better, in the first place I did not know this was a bundle of 4 courses, therefore it seems this course can be better enjoyed if you follow through in the correct order, although I did not feel jeopardized while I was watching the videos and doing the exercises. It might be useful to say that I am in my last year as an undergrad for engineering, so it was smoother to tackle the dense concepts of the last week, which is Fourier Transform, although I appreciated how the instructors introduced the subject allowing a first-timer to understand it.

I am still developing my code skills, thus I expected a great challenge when I saw the word "Advanced", however in reality, I went through the tasks and exercises almost effortlessly, but the last one which felt a bit more engaging. Hence, if I could just propose one enhancement, I would propose more challenging coding exercises. In brief, the classes are clear and easy to follow, the exercises lack that right measure of challenge and are not enough, and you could complete it in a week or two just dedicating a couple of hours per day.

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: Youdinghuan C

•Jun 12, 2020

This is a great course. The first 3 weeks covered basics of machine learning in a succinct fashion. The programming assignments were so self-explanatory and really helped reinforce my PySpark & Watson Studio skills. The quizzes were short, and some of them quite thought-provoking. The last week on Signal processing was excellent -- the instructor did a great job using rather brief amount of time to cover dense examples with python demos.

автор: Rishi P

•Apr 20, 2020

This course is really spectacular. This course gave me an understanding implementation of signal processing with machine learning. This gives an introduction to handling IBM Watson and coding assignment. You get a clear cut on machine learning implementation through this course.

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: Saurabh M

•Jun 25, 2020

The concepts were very well explained . Each algorithm is explained well- with the inner workings, the math behind them and practical applications. Te programming assignments were very helpful to actually get stuff done by myself!

автор: Mark M

•Apr 29, 2020

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.

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: Pravesh S

•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.

автор: Yerriswamy T

•Apr 28, 2020

Very good course and clear. It helped in revisiting many concepts of Machine Learning and signal processing. Programming sections are well structured and easy to work. Thank you teachers.

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: Jeevan P

•Jun 12, 2020

The information obtained through this course was excellent.Enjoyed learning through this course. Thanking both the professors for making this course an enjoyable learning experience.

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: AKSHAY K C

•Mar 07, 2020

A really good course on advanced topics of machine learning and signal processing with an in-depth explanation of each topic very clearly.

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