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

4.7
stars
235 ratings
39 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

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.

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.

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1 - 25 of 39 Reviews for Machine Learning Algorithms: Supervised Learning Tip to Tail

By Luiz C

Sep 11, 2019

Had higher expectations. Concepts not well and clearly explained. Notebooks bugged (we are actually warned about it), but even so not so interesting. Plan of the Course not so rational: why include the one section about model parameters on its own, rather than for each model.

I give it a 3 as the Instructor is smily and engaging, but it's a 2.5 mark (I have done another ML MOOC on another concurrent platform about the same topic, and the quality was much higher)

By Efren C

Jan 13, 2020

Excellent course, I was looking for a course which didn't explore advance math or go into the specifics of a particular ML method but which focuses on the main differences among then and teach about the whole process of M, this is the best course for that.

By S. k

Apr 12, 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.

By Dishant S

May 7, 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.

By Chih-Ta W

Sep 30, 2020

Great course, easy to grasp the main idea of how to assess and tune the performance of question-answering machines learned by machine learning algorithms through data

By Alvaro V

Jul 11, 2020

Very important concepts about supervised ML are presented. Really liked the course but a little stressed about the graded quices, even though I enjoyed very much.

By Fahim F

Apr 17, 2020

Great course but less in-depth knowledge about each of the hyper parameters and under the hood view of Algorithms.But excellent. Thanks!!!!!!

By Sornamuhilan S P

Jun 19, 2020

A great short capsule course to get overall bird view on Supervised learning. Much needed one for both practitioners and new beginners.

By KAZI S S

Jun 14, 2020

although the course felt a little hurried, I found the course and the instructor to be very engaging. I look forward to learning more

By Bishrul H

Jun 5, 2020

It's a nice course for those who likes to learn the supervised machine learning algorithms with practical experience.

By Kevin A D G

May 10, 2020

The explanation of the topics are easy to understand due to the dynamics of theory, practical exercises and quizzes.

By Vinayak D

Sep 1, 2020

really good, wish it had covered random forest and decision trees and other supervised models as well.

By Emilija G

Jan 9, 2020

The whole specialization is extremely useful for people starting in ML. Highly recommended!

By Munem

Jun 23, 2020

Easy and engaging. But would loved it more if some more coding examples were given.

By Brett S

Oct 4, 2020

Excellent instruction. One of the best in ML. Could use a bit more python though.

By Valerii M

Mar 31, 2020

Nice course! Good idea to add more practice with Jupyter Notebooks!

By M J

Oct 30, 2019

Great course! I received so much useful information from AMII.

By Miguel A S M

Oct 15, 2019

Excellent.

Teach you practical stuff that other courses don't.

By Hamza M

May 2, 2020

A good refresher on some commonly found learning algorithms.

By Dinesh K

Oct 4, 2020

Great learning..Talked almost all important issues.

By SATHEESH K G

Jun 28, 2020

Good content and nicely delivered!

By Saulo A G S

Oct 29, 2020

I learn many new concepts

By Cheng H Z

Oct 10, 2019

Explained things clearly

By Rimmon S B

Oct 1, 2020

Really cool teaching!

By Danilo C D C J

Sep 17, 2020

Nice course!