Der iTunes Store wird geöffnet.Falls iTunes nicht geöffnet wird, klicke auf das iTunes Symbol im Dock oder auf dem Windows Desktop.Progress Indicator
Apple Books wird geöffnet.Falls Apple Books nicht geöffnet wird, klicke im Dock auf die Bücher-App.Progress Indicator

iTunes is the world's easiest way to organise and add to your digital media collection.

iTunes wurde auf Ihrem Computer nicht gefunden. Jetzt iTunes holen, um Inhalte aus dem iTunes Store zu laden.

iTunes ist schon installiert? Klicke auf „Ich habe iTunes“, um es jetzt zu öffnen.

I Have iTunes

Machine Learning

von Stanford

Dieses Kursmaterial steht nur in der iTunes U-App auf iPhone oder iPad zur Verfügung.


This course provides a broad introduction to machine learning and statistical pattern recognition.

Topics include: supervised learning (generative/discriminative learning, parametric/non-parametric learning, neural networks, support vector machines); unsupervised learning (clustering, dimensionality reduction, kernel methods); learning theory (bias/variance tradeoffs; VC theory; large margins); reinforcement learning and adaptive control. 
The course will also discuss recent applications of machine learning, such as to robotic control, data mining, autonomous navigation, bioinformatics, speech recognition, and text and web data processing.

Students are expected to have the following background:

- Knowledge of basic computer science principles and skills, at a level sufficient to write a reasonably non-trivial computer program.

- Familiarity with the basic probability theory. (Stat 116 is sufficient but not necessary.)

- Familiarity with the basic linear algebra (any one of Math 51, Math 103, Math 113, or CS 205 would be much more than necessary.)

This Stanford course was taught on campus twice per week in 75 minute lectures for the Stanford Engineering Everywhere Initiative.

For more online learning opportunities, please visit Stanford Online.


Man kann nie Genug Wissen ! / you will never ever know enough!

you will never ever know enough!
and thats why every one should be able to find some minutes in his live to learn even more...


Was geht?
Ich mach mal den Kurs hir mit

Machine Learning
In iTunes ansehen