What is focus numeric?

Eric Johnson's Data Science Site!


I hope that someone out there finds this site interesting. Items posted here are not tutorials - but feel free to use them as such if you wish. I have tried to remain informal (assuming that most visitors won't be mathematicians) but have tried to keep my language precise and mathematically correct. In every case I explain what I'm doing so that any careful reader will be able to follow the logic if not the math.

Most of the items on this site are math-oriented. I want to focus on machine learning so please stay tuned for more content.

What is not on this site...

  • Any of the code I have written for clients.
  • Any work that I paid to do or did at my regular job. All work posted here is my own and belongs solely to me.
  • Any of my ideas for websites, implementations of technologies and anything that is my valued intellectual property. You may do whatever you wish with any of the code, etc.
If you have any questions about this site or things posted here please feel free to contact me.

What is here?

Site Contents!

  • home: Home sweet home. You're here now!
  • items: These are examples of mathematics and data science work by me.
  • about: Information about this site, in general. There is also information about what tools I am using.
  • else: Hmmm... Other stuff.
  • resume: Resumé.

Math on this site is rendered with Math Jax and \( \LaTeX \) . Here are some sample equations.

\(g \in \bigcup_{n=1}^{\infty} U_{n, \varepsilon} \ \therefore \ g \in C(x)\),
\( \| x \|_p = \left( \displaystyle\sum_{i=1}^n \vert x_i \vert^p \right)^{1/p}\),
\( \ \ \ A_{m,n} = \begin{pmatrix} a_{1,1} & a_{1,2} & \cdots & a_{1,n} \\ a_{2,1} & a_{2,2} & \cdots & a_{2,n} \\ \vdots & \vdots & \ddots & \vdots \\ a_{m,1} & a_{m,2} & \cdots & a_{m,n} \end{pmatrix}\), \( \ \ \ \displaystyle\int_\Omega x \cdot f(x) \ dx = 1 \)

Most recent item: How fast does this TSP algorithm work?

My skills and interests

  • Custom Machine Learning Algorithms.
  • Statistical and Numerical Analysis.
  • Data science technologies: Python, R, MongoDB, Elasticsearch, and more.
  • Technical Communications.
  • Artificial Intelligence.
  • Serverless and High Performance Computing.
  • I enjoy working on hard problems that require computers!

"Somewhere, something incredible is waiting to be known."

Carl Sagan

Here are some recent items. More is on the way!

Featured Items

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