Learner Reviews & Feedback for Machine Learning Algorithms: Supervised Learning Tip to Tail by Alberta Machine Intelligence Institute
About the Course
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, dict...
Top reviews
SK
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.
TH
May 15, 2022
This is an excellent course which goes into some depth on the different ML models and underlying complexity but it avoids getting bogged down into the details too much.
51 - 66 of 66 Reviews for Machine Learning Algorithms: Supervised Learning Tip to Tail
By CHILUKURU S A
•Oct 22, 2020
nice
By Ubeydullah K
•Nov 11, 2021
I am grateful to have attended this course. I have learned quite a lot and I believe, now, I have a solid general understanding of some of the most common ML algorithms. The instructor, Anna Koop is very knowledable and she has a very clear way of explaining the concepts. The reason why I haven't rated it 5-star is because the course is not really designed around practice. It is rather conventional in the sense that the instructor takes the central stage and students don't get to practice much. Quizzes are good, but they are far from being enough to give learners actual experience of "doing" machine learning. I am aware of the vastness of the field, and maybe that's why they kept the course intructor centered, but I still expect courses to push learners more in trying out the methods themselves and learning by doing. Still, the course is very beneficial and has valuable content. It is a great knowledge source as well. Warmest regards.
By Morgan S
•May 23, 2021
This course is a great overview of ML concepts. The professor is superb! I did not give 5 stars because the labs need to be improved. The labs are too simple. This course should provide more opportunities for applying the ML concepts.
By Andrey Z
•Dec 30, 2021
Good overview course. I hope authors will add more practice task in the futrure
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 Manikala L
•Mar 22, 2025
good
By Rahul M
•Dec 18, 2020
nice
By sandeep d
•Aug 27, 2020
nice
By Nicolas G
•Apr 17, 2021
High level overview of Machine Learning, poor examples and incomplete labs.
By PIYUSH G
•Apr 8, 2020
good
By Raghuram T
•Oct 10, 2020
It could have been better if the trainer had included more hands-on examples rather than just tuning the slides and most important algorithms and its usage was there in the attached links for reading and I felt if this could have been taught in the training rather than just a document to read and self learn the quality of the course would have been fantastic.
By Carlos E
•Oct 12, 2021
Doesn't explain in a good way the models used. Only explain how to use them. I really need the math and a deep explanation to understand how to use the function. This is like they just give you the documentation and do examples.