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Learner Reviews & Feedback for Machine Learning Algorithms: Supervised Learning Tip to Tail by Alberta Machine Intelligence Institute

4.7
stars
315 ratings
53 reviews

About the Course

This course takes you from understanding the fundamentals of a machine learning project. Learners will understand and implement supervised learning techniques on real case studies to analyze business case scenarios where decision trees, k-nearest neighbours and support vector machines are optimally used. Learners will also gain skills to contrast the practical consequences of different data preparation steps and describe common production issues in applied ML. To be successful, you should have at least beginner-level background in Python programming (e.g., be able to read and code trace existing code, be comfortable with conditionals, loops, variables, lists, dictionaries and arrays). You should have a basic understanding of linear algebra (vector notation) and statistics (probability distributions and mean/median/mode). This is the second course of the Applied Machine Learning Specialization brought to you by Coursera and the Alberta Machine Intelligence Institute....

Top reviews

SK
Apr 11, 2020

Excellent course. In which I had in-depth knowledge of all algorithms and the way she explained attracts to listen except for her spontaneity and speed in progressing.

DS
May 6, 2020

Excellent course for an overview of different ML algorithms. The course is made from a perspective of giving insights in process and not too many mathematical details.

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26 - 50 of 53 Reviews for Machine Learning Algorithms: Supervised Learning Tip to Tail

By KANALA J

Dec 7, 2020

Excellent Teaching!:)

By Rimmon S B

Oct 1, 2020

Really cool teaching!

By UPPUNURU K R

Dec 8, 2020

Great expilination

By KOTA V

Dec 6, 2020

good for learning

By AVASARALA S

Dec 7, 2020

Learnedly well

By D V R

Dec 23, 2020

Great Course

By Danilo C D C J

Sep 17, 2020

Nice course!

By kaki m p

Dec 16, 2020

good course

By KONDAPALLI D

Nov 11, 2020

great!

By 121710317007 C J

Dec 12, 2020

good

By MATTHURTHI P V D R

Dec 12, 2020

good

By Harika B L

Dec 9, 2020

good

By Gayathri

Dec 9, 2020

good

By KANDULA J C

Nov 21, 2020

good

By VUPPUTURI R K

Oct 28, 2020

Good

By CHILUKURU S A

Oct 22, 2020

nice

By Kham H Y

Oct 28, 2020

Learn some valuable insights on scikit-learn capabitlity through the labs

By nouran a

May 7, 2020

Many useful information but need some more explanation, overall awesome

By Saksham G

Apr 4, 2020

More maths to explain the underlying concepts will be good!!

By Daniel W

Nov 28, 2020

Machine learning concepts are introduced well.

By Grecia P

Mar 3, 2020

week two was heavy

By Marru R

Dec 18, 2020

nice

By sandeep d

Aug 27, 2020

nice

By Enyang W

Feb 21, 2020

This course covers lots of important ideas and knowledges for Machine Learning practitioners. It is definitely nice to deal with topics such as grid search or scikit-learn, but I think the course only covers these topics in a nutshell, it is more superficially discussed. If you are interested in Machine Learning, you should definitely bring your own motivation to dive deeper into those topics.. Also, Dr. Koop speaks very very fast though.. I attended courses by Andrew Ng, his courses provide a way better comprehensibility for listeners. The notebooks are a bit weird, very easy to understand and are hence not challenging. If you really want to understand the algorithms deeply, I don't think this course is the right one. But all in all, I completed the course, but I don't think I was able to understand everything by taking the course only.

By Varun M S

Jun 25, 2020

The content was good but the videos went too fast and too much theory was involved. For a beginner it was too much to take. I was expecting some Practical and programming aspects in Quizzes and tests but that is okay. Overall a good experience