|location||San Francisco, CA|
|visits||member for||3 years, 8 months|
|seen||May 2 at 8:38|
i build Systems & Tools for Analysis, Prediction, Visualization, & Simulation.
i also design, code, and deploy complete Machine Learning-based applications (e.g., anti-fraud filter, recommendation engine, monitoring/anomaly detectors), usually designed as modular internal thrift services decoupled from the main app.
Machine Learning: in particular, recursive descent parser (CART/C4.5), Multi-layer Perceptron, SVM/SVR, Kernel Machines, kNN/kdtree, Probabilistic Graphical Models (eg, Markov Random Field)
Dimension Reduction Techniques: spectral decomposition (PCA & kPCA, kLDA), Kohonen Map (self-organizing map)
Social Network Analysis & Visualization: using graph theoretic techniques for e.g., community detection, id of members essential for network health/growth; identify nascent sub-communities; (particular fluency GraphViz, the premiere tool for graph layout/visualization, NetworkX, the primary network analysis library for python, and d3).
Analysis & Modeling of Time-Dependent Data
Optimization: Combinatorial Optimization and Constraint-Satisfaction Programming
Numerical Methods: e.g., matrix decomposition, Monte Carlo techniques, Gaussian quadrature, finite difference methods
Data Modeling for "Non-Relational" systems (in particularly Redis and MongoDB) and for relational (ROLAP), multi-dimensional (MOLAP), and hybrid (HOLAP) Data Warehouse systems using conventional relational/SQL servers.
- SciPy + NumPy + Matplotlib
- HDF5 (& pytables, hfpy)
- flask/werkzeug (python web framework)
- storm (distributed processing)
- d3.js (svg-based primitives for rendering plots in the browser)
- git (& gitHub)
|bio||website||careers.stackoverflow.com/…||visits||member for||3 years, 8 months|
|location||San Francisco, CA||seen||May 2 at 8:38|