typeviz.com

numerics.io

Science Archives - Algorithms | Science | Code

http://numerics.io/category/science

Numerics library for .Net. QFT in a nutshell. April 1, 2014. The whole of QFT can be summarized really into this basic formula:. Quantum field theory is so irritating and fun at the same. It’s a bag full of toys, delights, tricks, broken tools, uninteresting pieces, difficult gears and splendid inventions. It’s esoteric and deep, it’s a miracle that all of this actually does work and seems to be used by Nature. A kaleidoscope from F# and monads. April 1, 2014. In a related article. Which at first sight d...

numerics.io

Tip Archives - Algorithms | Science | Code

http://numerics.io/category/tip

Numerics library for .Net. July 2, 2014. There is definitely as lot of fun in the new Mathematica 10 and the Cloud. Machine learning is so easy to apply, it’s stunning. At the same time, the magic does not make the output automatically true. A quick and simple test reveals some fun facts;. Great fun at the swimming pool". C'est plus beau quand c'est inutile". Stairs have no orientation". My daughter left early today". This black-box classification should have been amplified with at least some hints about...

numerics.io

Katz centrality - Algorithms | Science | Code

http://numerics.io/katz-centrality

Numerics library for .Net. April 3, 2014. Take an arbitrary network, preferably a directed one, and ask yourself; what is the most important node in this network? The question appears in all sorts of contexts; data networks (what is the critical hub? Social networks (who is the influential person? Epidemic networks (who is spreading the virus? Take a node and assign to the adjacent node a weight. To the next level of children/siblings assign. And so on. In other words. Is the largest eigenvalue of A we d...

numerics.io

1001 ways to create graphs in Mathematica - Algorithms | Science | Code

http://numerics.io/1001-graphs

Numerics library for .Net. 1001 ways to create graphs in Mathematica. September 3, 2014. This is an overview of the many ways in which one can create graphs in Mathematica. It demonstrates the ubiquity of graphs and how Mathematica. Makes it easy to experiment with ideas. At the same time, various Mathematica. Symbols and techniques are presented which we will cover more in depth in later article. And unwrap its faces. The number of vertices can be found in two ways here, either using the VertexCount.

numerics.io

Tip: some classification - Algorithms | Science | Code

http://numerics.io/classification-issues

Numerics library for .Net. July 2, 2014. There is definitely as lot of fun in the new Mathematica 10 and the Cloud. Machine learning is so easy to apply, it’s stunning. At the same time, the magic does not make the output automatically true. A quick and simple test reveals some fun facts;. Great fun at the swimming pool". C'est plus beau quand c'est inutile". Stairs have no orientation". My daughter left early today". This black-box classification should have been amplified with at least some hints about...

numerics.io

Numerics, Author at Algorithms | Science | Code

http://numerics.io/author/numerics

Numerics library for .Net. All posts by Numerics. Time series in R. October 17, 2015. April 10, 2015. Gradient boosting machine learning. March 2, 2015. The similarity with a basis of functions in an Hilbert space is sometimes difficult to push aside. If we have weak learners. Then an exact learner would be. But you immediately face the questions. What kind of space is F sitting in. What is the inner-product in this space which articulates the basis. An approximation F of the full function. Makes it easy...

numerics.io

Gradient boosting machine learning - Algorithms | Science | Code

http://numerics.io/gradient-boosting

Numerics library for .Net. Gradient boosting machine learning. March 2, 2015. The similarity with a basis of functions in an Hilbert space is sometimes difficult to push aside. If we have weak learners. Then an exact learner would be. But you immediately face the questions. What kind of space is F sitting in. What is the inner-product in this space which articulates the basis. How would one in general reformulate the analogy within category theory. An approximation F of the full function. Time series in R.

numerics.io

Representing graphs in F# - Algorithms | Science | Code

http://numerics.io/fsharp-graphs

Numerics library for .Net. Representing graphs in F#. April 3, 2014. From a purely mathematical point of view you can idealize nodes and connections but from a more practical point of view it’s useful to associate to a node some payload or data:. Some concrete data which adds a dimension to the node related to the business context. For example, you could attach Twitter user information or a geographic tag or even an image. We will define in F# a node as a combination of these two elements:. A connection,...