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Learner Reviews & Feedback for Data for Machine Learning by Alberta Machine Intelligence Institute

4.3
stars
72 ratings
18 reviews

About the Course

This course is all about data and how it is critical to the success of your applied machine learning model. Completing this course will give learners the skills to: Understand the critical elements of data in the learning, training and operation phases Understand biases and sources of data Implement techniques to improve the generality of your model Explain the consequences of overfitting and identify mitigation measures Implement appropriate test and validation measures. Demonstrate how the accuracy of your model can be improved with thoughtful feature engineering. Explore the impact of the algorithm parameters on model strength To be successful in this course, 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 third course of the Applied Machine Learning Specialization brought to you by Coursera and the Alberta Machine Intelligence Institute....

Top reviews

BS
Oct 11, 2020

Some bugs in the assignment, but overall excellent discussion of how to avoid common pitfalls when using data for ML.

EG
Jan 8, 2020

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

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1 - 18 of 18 Reviews for Data for Machine Learning

By Emil K

Mar 22, 2020

The instructor is great, but please fix the programming assignment! There are so many typos it's embarassing. Also, the autograder EXPECTS typos in some variable names, so you can't even pass it if your answers are correct.

By Hari N L

Jun 26, 2020

The experience with the programming assignment was very bad. There was an error that was occurring at frequent intervals which crashed my jupyter notebook, making me to start afresh. I was facing an issue in reopening the notebook where it took a long time and the mathematical notations were also not loaded properly.

By Brett S

Oct 12, 2020

Some bugs in the assignment, but overall excellent discussion of how to avoid common pitfalls when using data for ML.

By Emilija G

Jan 9, 2020

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

By Camilo A C F

Jul 5, 2020

Good course, if you follow the previous ones and if you know some python (Pandas).

By Miguel A S M

Dec 1, 2019

What is different about this course is its focus of ML applied to the real world.

By Naruki H

Jul 17, 2020

Excellent content with good programming assignments and examples.

By Tony J

Jul 17, 2020

This is the best!!!

By Valerii M

Mar 31, 2020

Nice course!

By Eshani A

Nov 28, 2020

It's a really nice course covering all the content related to data in Machine learning. The content is so detailed and the instructor have made the entire learning process very smooth. Thanks a lot for such a great course.

By Pratama A A

Jun 8, 2020

Well this course absolutely good,but you need patience when doing programming assignment,and there's a lot error tho,but what we need is that information,anna gave us the easiest insight

By SHREYAS C

Jun 12, 2020

Really good,... one thing you have to change is that your assumption of people knowing Python for Jupyter Notebook really well... the week 3 assignment was a pain for quite sometime

By Abdullah A

Dec 24, 2019

the course is very powerful and I have jump to higher level regarding data wrangling and how to deal with data. the assessment have some error which can be fixed easily

By Kham H Y

Oct 31, 2020

The programming assignment was tough, the instructions were a bit misleading. I didn't get all correct though.

By Danijel T

Jul 22, 2020

The instructor is knowledgable and materials are moderately useful.

Notebook with assignment is broken. There are many typos and elements which are not rendered properly. Notebook is huge and every subtask depends on previous state. It takes time to reload all previous tasks if you did not solve everything in one go. Final quiz basically repeats all the questions from previous quiz.

Course could use more polish.

By Halil T

Sep 18, 2020

deeply theoretical but excellent assignment file (good review for pandas library )

By Jhon F B L

Apr 25, 2020

The course is great but the courser a notebooks were a nigthmare

By Lam C V D

Aug 26, 2020

Bad Grader system and complicated coding taught. Instructions given unclear and no instructor support at all.