doug
i build Systems & Tools for Analysis, Prediction, Visualization, & Simulation.
i also design, code, and deploy complete distributed and (horizontally) scalable Machine Learning-based applications (e.g., anti-fraud filter, recommendation engine, monitoring/anomaly detectors), often in the service layer decoupled from the main app.
Techniques:
- Machine Learning
- decision tree (CART/C4.5) & random forest
- deep learning (multi-layer perceptron)
- support vector machine (SVM/SVR)
- kNN/kdtree
- probabilistic graphical models (eg, Bayesian Net, Markov Random Field)
- Dimension Reduction Techniques
- spectral decomposition (PCA & kPCA, kLDA)
- Kohonen Map (self-organizing map)
- ETL pipelines
- akka stream
- Apache Spark
- Kafka/Zookeeper
- Social Network Analysis & Visualization
- using graph theoretic techniques for
- community detection
- identify members essential for network health/growth
- identify nascent sub-communities
- particular fluency in NetworkX, GraphViz
- using graph theoretic techniques for
- Analysis & Modeling of Time Series
- decomposition
- forecasting
- anomaly detection
- Optimization
- combinatorial optimization
- csp
- Numerical Methods
- matrix decomposition
- monte carlo techniques
- Gaussian quadrature,
- finite difference methods
- Persistence
- redis
- postgres
- Geo-Spatial Data Modeling, Persistence, & Computation
- postgis (storage, query, computation)
toolchain:
- scala
- scalaz
- akka & akka-stream
- python
- NumPy + SciPy + Matplotlib + pandas
- cython
R
vagrant
git (& gitHub)
- travis ci
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Palo Alto, CA
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Member for 10 years, 8 months
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Last seen Jul 22 '16 at 1:23
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