Every course from every provider we track, with the same filters over all of them: level, length, price, certificate and who stands behind it.
34 courses for “Statistics in Machine Learning”
2 hours
6 lessons, 149 minutes in all, from YouTube.
13 hours
15 lessons, 803 minutes in all, from YouTube.
New courses, a couple of emails a month. One click unsubscribes.
4 hours
Automotive Engineering Fundamentals
32 lessons, 267 minutes in all, from YouTube.
13 hours
27 lessons, 794 minutes in all, from Mechanical Engineering E-Learning.
1 minutes
A 1-minute video from Ansys Learning.
2 minutes
A 2-minute video from The Learning Studio.
2 minutes
A 2-minute video from The Learning Studio.
3 minutes
A 3-minute video from The Learning Studio.
18 minutes
Continuous integration applied to machine learning, in under twenty minutes.
45 minutes
Forty-five minutes of scikit-learn, from fitting a model to scoring it.
13 minutes
Thirteen minutes on how a model is judged, and why accuracy alone is rarely the answer.
13 minutes
What machine learning is, explained without the mathematics, in thirteen minutes.
12 hours
Eleven hours of statistics and probability for data science, from first principles.
2 hours
Two hours of R, taught as what it is: a language built for statistics.
10 hours
Ten hours of business analytics, from the statistics through to the dashboards.
24 hours
Twenty-four hours of business analytics: the statistics, the tools and the reporting.
57 minutes
The opening lecture of MIT's introductory deep learning course.
9 hours
Eight and a half hours on deep learning, from neural networks to the frameworks that train them.
10 hours
Ten hours of deep learning from Edureka, from the neural network up.
1 hour
An hour on descriptive statistics: the measures that summarise a dataset before any model touches it.
