state-space distributions and decisions
Project description
uncertainty and confidence, distributions, their evolution with time, noise, and observations, tracking and detection, decisions, risk and the cost of errors, model-based systems, sample-and-propagate, sequential monte-carlo, markov-chain monte-carlo
The Flaw of Averages: Why We Underestimate Risk in the Face of Uncertainty, Sam L. Savage
Bayesian Signal Processing: Classical, Modern, and Particle Filtering Methods, James V. Candy
Kalman Filtering: Theory and Practice, Mohinder S. Grewal, Angus P. Andrews
Forecasting, Structural Time Series Models and the Kalman Filter
current focus is automated build-test-deploy to kubernetes-engine using cloud-source and cloud-build along the way.
automated build-test-deploy to pypi is mostly a placeholder, ubuntu clone-install-develop of gitlab repo is assumed for now.
sudo apt-get -qq update -qy
sudo apt-get -qq install -y python3.6 python3-venv python3-pip
git clone git@gitlab.com:noahhsmith/statespace.git statespace
cd statespace
python3 -m venv venv
. venv/bin/activate
python3 setup.py develop
pytest
python3 statespace --demo
cloud stuff
gcloud auth login
gcloud projects list
source cloud.env
gcloud config set project statespace-233406
gcloud beta container --project $PROJECT clusters create $CLUSTER --zone $ZONE
kubectl create -f services.yaml
kubectl create -f ingress.yaml && kubectl create -f deployments.yaml && kubectl create -f secrets.yaml
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