A simple binary classification Neural Net implementation
stack initstack build --pedanticContinuous:
stack build --pedantic --file-watchOnly one executable:
stack build neural-net:exe:image-eg --pedantic --file-watchstack test --pedanticWith watching of files for changes
stack test --file-watch --pedanticWith error stack traces
stack test --pedantic --file-watch --profileWith more tracing
stack test --pedantic --file-watch --trace .stack exec neural-net-exe -- --helpSimple Logistic Regression example:
stack exec logreg -- -c -l 0.005 -i 1000 examples/simple-csv/train.csv examples/simple-csv/test.csvBinary image classification Log Reg example (requires copying in some files to /examples):
stack exec image-logreg -- -l 0.005 -i 1000 \
examples/images/nn-course-train/1 \
examples/images/nn-course-train/0 \
examples/images/nn-course-test/1 \
examples/images/nn-course-test/0Binary image classification Deep NN example (requires copying in some files to /examples):
stack exec image-deep -- -l 0.0075 -i 2500 \
examples/images/nn-course-train/1 \
examples/images/nn-course-train/0 \
examples/images/nn-course-test/1 \
examples/images/nn-course-test/0stack build neural-net:exe:image-deep --pedantic --profile
stack exec image-deep -- -l 0.0075 -i 2500 \
examples/images/nn-course-train/1 \
examples/images/nn-course-train/0 \
examples/images/nn-course-test/1 \
examples/images/nn-course-test/0 \
+RTS -p