House in Koamicho

"The statistician cannot evade the responsibility for understanding the process he applies or recommends." -- Ronald A. Fisher

"Study without desire spoils memory, and it retains nothing that it takes in." - Leonardo da Vinci

Smart Sand

Decorative Plywood

So long, and thanks for all the memories!

Focusing Sound Waves

Where is Waldo?

Inline Conrete

A Lovely Turnip!

JINC Function

Baixa House in Lisbon

Awesome Studios 1 Awesome Studios 2

Centrifugal Governor

Lovely Printing

House BM

Metronome Synchronization 1 of 2

Metronome Synchronization 2 of 2

J

Japanese Multiplication

Library Architecture

KCV House

Nice

House Tokyo

Chevron House

More's Law

Charles Limb: Building the musical muscle #TED http://on.ted.com/A21f

Pachube

Evelyn Glennie - TED Talks

Mark Changizi

Standard University, Fall 2011 - Free On-line Machine Learning Course

Our Internet access rates...

Insight.

University of Iowa - Phonetics

Kalman Filtering

Lago di Olginate, Italy - National Geographic

I must find time to have a look...

A machine learning link...

My little friend.

A different, engaging perspective.

I feel ill.

Wind Farm Evolutionary Algorithms - Cool!

Wow!

The Simple Life - The Turtleman from Kentucky

Ikepod - Perhaps, one day.

Buzz!

Semi-supervised Learning, Manifold Methods

Semi-supervised Learning - videolectures.net

Semi-supervised Learning, Manifold Methods

Semisupervised Learning Approaches

L.A. Traffic, 24 Hour Window

Typical.

Fun, fun, fun!

"a liberal dose of self-congratulatory delusion..." - Rik Emmett

I always knew the Light-side of the Force was better... ;)

Twilight Landing At LAX (Cockpit View)

Unsupervised Feature Learning and Deep Learning -
Andrew Ng

Reminds me of the scene in "Big" with actors Tom Hanks and Robert Loggia. A new twist, for sure.

Likely?

Carl Friedrich_ Gauss (circa 1828, Wiki - Least Squares

Matlab Code - "Neural Networks and Learning Machines," 3rd Edition

Three Aspects to Tackling a Research Problem - Simon Haykin

-Dig deeply into the literature relating to your problem and thereby determine what other researchers have contributed to it.

-Try to define the important issues involved in your problem. In this context, remember that in developing a proper understanding of the problem, you will have almost solved it.

-In solving the problem, the aim should be to make a significant difference to the literature.

The Selfish Giant - Oscar Wilde

"Each time we face a fear, we gain strength, courage, and confidence in the doing." - Unknown

Wynton Marsalis, Hummel Concerto in E, 3rd Movement

Neptune Canada

I love learning!

When the human element gets you down...

Ho, ho, ho!

Hans Rosling - Making Data Dance

The growth of 200 Countries across 200 years in 4 minutes.

Inverse Pendulum - Cool!

National Geographic - Traveler

Optimal

Non-Uniform Random Variate Generation

Particle Filters

Simon Godsill

2 videos

Bayesian inference and Gaussian processes

Carl Edward Rasmussen

6 videos

Gaussian Process Basics

David MacKay