Videos 4x4 - Baye videos

Bayes on Blogs - 22

Duración: 2:2
Calificación: n/a
Visto:
Autor: MrToxichazard

Tags: back Bayes Blog Blogging Crazybayes is Webcam yay

Im back guys! I managed to fix my webcam. Apparently my new USB headset was using up all the bandwith or virtual memory or whatever, so Ive had to resort to using the microphone built into the monitor. Nothing to special just letting you know that im still alive and kicking. ill be back tomorrow...

'Destroyer' - 2000 - Core Culture #9 - Part 3

Duración: 4:40
Calificación: n/a
Visto: 44
Autor: Lat34

Tags: Ali Andrew Baye Blaise Bozung Carrier Chad Crawford David Dunn Goulet Huffman J2 Jason Jenke Jeremy Jordan Kevin Lukas Max McAlister McConnaughy Mendenhall Mitch Nate Nelson Otterstrum Porsheron Rasmus Risto Rob Rosenthal Sansalone Scott Scotty Shannon Wittlake

An in-depth look at the unreal snowboard film 'Destroyer' from Kingpin Productions. Watch some of your favorite riders like Todd Richards, Jeremy Jones, Barret Christy, Tyler Lepore, Josh Dirksen and Mikey Leblanc take on the snow in a film that will make your mind spin. Director Whitey is...

Lecture 5 | Machine Learning (Stanford)

Duración: 75:31
Calificación: n/a
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Autor: stanforduniversity

Tags: algorithm analysis Bayes computer digression discriminative engineering Gaussian generative Laplace learning math naive robotics science smoothing technology

Lecture by Professor Andrew Ng for Machine Learning (CS 229) in the Stanford Computer Science department. Professor Ng lectures on generative learning algorithms and Gaussian discriminative analysis and their applications in machine learning. This course provides a broad introduction to...

Lecture 13 | Machine Learning (Stanford)

Duración: 74:57
Calificación: n/a
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Autor: stanforduniversity

Tags: algorithm analysis Bayes computer digression distribution EM engineering expectation factor Gaussian learning math maximization mixture model naive robotics science technology unsupervised

Lecture by Professor Andrew Ng for Machine Learning (CS 229) in the Stanford Computer Science department. Professor Ng lectures on expectation-maximization in the context of the mixture of Gaussian and naive Bayes models, as well as factor analysis and digression. This course provides a broad...

Lecture 6 | Machine Learning (Stanford)

Duración: 73:9
Calificación: n/a
Visto:
Autor: stanforduniversity

Tags: algorithm Bayes Bernoulli computer engineering event learning machines math model multinomial multivariate naive networks neural robotics science support technology vector

Lecture by Professor Andrew Ng for Machine Learning (CS 229) in the Stanford Computer Science department. Professor Ng discusses the applications of naive Bayes, neural networks, and support vector machine. This course provides a broad introduction to machine learning and statistical pattern...