Chevron Left
Retour à Machine Learning Algorithms: Supervised Learning Tip to Tail

Avis et commentaires pour d'étudiants pour Machine Learning Algorithms: Supervised Learning Tip to Tail par Alberta Machine Intelligence Institute

403 évaluations

À propos du cours

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....

Meilleurs avis


14 mai 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.


11 avr. 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.

Filtrer par :

51 - 65 sur 65 Avis pour Machine Learning Algorithms: Supervised Learning Tip to Tail


22 oct. 2020

par Ubeydullah K

11 nov. 2021

par Morgan S

23 mai 2021

par Andrey Z

29 déc. 2021

par Kham H Y

28 oct. 2020

par nouran a

7 mai 2020

par Saksham G

4 avr. 2020

par Daniel W

28 nov. 2020

par Grecia P

3 mars 2020


18 déc. 2020

par sandeep d

27 août 2020

par Nicolas G

17 avr. 2021


8 avr. 2020

par Raghuram T

10 oct. 2020

par Carlos E

12 oct. 2021