OpenCourser is compensated by Coursera. Learn more.
This course teaches valuable skills
Estimated earnings for individuals who use skills taught in this course. Figure based on US average salary and career skills data.
Write a review
Reviews for this course
Amazing. I learned regression (linear and logistic), k-means clustering, and principal components analysis in uni, but seeing it in an ML context reinforced the grasp I have over those topics. Neural networks were entirely new to me and by far one of the most interesting concepts I've learned from anywhere!
What learners are saying BETA
support vector machines
Topics include: Supervised learning (parametric/non-parametric algorithms, support vector machines, kernels, neural networks)…
The course broadly covers all of the major areas of machine learning -…
For example, for Support Vector Machines and backpropagation for neural networks.
… logistic regression, Support Vector Machines (SVM), anomaly detection, non-supervised learning (clustering, K…
mentor tom mosher
Course mentor Tom Mosher's contributions are particularly valuable.Great material and teaching style…
hours per week
...I imagine I will have to learn other programming languages after this course.As for time…
I would probably budget at least 5 hours per week.
I think I spent about 20 hours per week to try to absorb the material.
I would estimate that it took about 4-5 hours per week to complete…
balance between theory
It has a perfect balance between theory and practice.
!I wish there was a training exercise for weeks 10-11…
Great balance between theory and practical examples.Very high quality lectures and exercises …
There is a good balance between theory and practice, with programming assignments most weeks.
The topics were very tractable.Complex concepts explained with ease and clarity…
knew nothing about
...some can still be quite challenging.I knew nothing about ML before I joined…
I knew nothing about Machine Learning before starting the course.
I knew nothing about ML and now comfortable with ML.
You can find this course in these lists:
Courses like this