Machine Learning Algorithms
Supervised Learning Tip to Tail
Machine Learning: Algorithms in the Real World,
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.
Get a Reminder
| Rating | 4.4★ based on 7 ratings |
|---|---|
| Length | 5 weeks |
| Starts | Jul 3 (43 weeks ago) |
| Cost | $99 |
| From | Alberta Machine Intelligence Institute via Coursera |
| Instructor | Anna Koop |
| Download Videos | On all desktop and mobile devices |
| Language | English |
| Subjects | Programming Data Science Business |
| Tags | Computer Science Data Science Business Algorithms Machine Learning Business Strategy |
Get a Reminder
Similar Courses
What people are saying
excellent.teach you practical stuff
Excellent.Teach you practical stuff that other courses don't.
advance math or go
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.
main differences among then
each model.i give
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)
information from amii
I received so much useful information from AMII.
2.5 mark
good coverage
Good coverage of the topics in supervised learning.
notebooks bugged
Notebooks bugged (we are actually warned about it), but even so not so interesting.
actually warned
concurrent platform
courses do
explore advance
Careers
An overview of related careers and their average salaries in the US. Bars indicate income percentile.
Research Scientist-Machine Learning $55k
Cloud Architect - Azure / Machine Learning $75k
Watson Machine Learning Engineer $81k
Machine Learning Software Developer $103k
Software Engineer (Machine Learning) $116k
Applied Scientist, Machine Learning $130k
Autonomy and Machine Learning Solutions Architect $131k
Applied Scientist - Machine Learning -... $136k
RESEARCH SCIENTIST (MACHINE LEARNING) $147k
Machine Learning Engineer 2 $161k
Machine Learning Scientist Manager $170k
Machine Learning Scientist, Personalization $213k
Write a review
Your opinion matters. Tell us what you think.
Please login to leave a review
| Rating | 4.4★ based on 7 ratings |
|---|---|
| Length | 5 weeks |
| Starts | Jul 3 (43 weeks ago) |
| Cost | $99 |
| From | Alberta Machine Intelligence Institute via Coursera |
| Instructor | Anna Koop |
| Download Videos | On all desktop and mobile devices |
| Language | English |
| Subjects | Programming Data Science Business |
| Tags | Computer Science Data Science Business Algorithms Machine Learning Business Strategy |
Similar Courses
Sorted by relevance
Like this course?
Here's what to do next:
- Save this course for later
- Get more details from the course provider
- Enroll in this course
