HTTPS SSH
# julia_training Code for the Kaggle Competition [Getting Started with Julia](https://www.kaggle.com/c/street-view-getting-started-with-julia) for the team [Data Science Saigon](https://www.kaggle.com/t/184705/data-science-saigon) ## Files ### Tutorials (iJulia notebooks display better on github) * /docs * /docs/[DataFramesWithJulia.ipynb](https://github.com/AppTrain/julia_training/blob/master/DataFramesWithJulia.ipynb) * /docs/Machine Learning with Julia.ipynb(https://github.com/AppTrain/julia_training/blob/master/Machine%20Learning%20with%20Julia.ipynb) ### Julia Code * convert.jl ## Script to store .bmp files in _data/trainResized_ in a single hdf5 file _data/train.hdf5_ * con.jl ## alternate to convert.jl. Demonstrates breaking training data into train and test sets. * knn\_julia\_tutorial.jl Code from Kagle [KNN tutorial](https://www.kaggle.com/c/street-view-getting-started-with-julia/details/knn-tutorial) tweaked to work with Julia 3.8 * rf\_julia\_benchmark.jl Code from Kagle [Julia tutorial](https://www.kaggle.com/c/street-view-getting-started-with-julia/details/julia-tutorial) tweaked to work with Julia 3.8 * **mocha\_intro.jl** core file for creating a submission for this competition, base on the [Mocha Turorial](https://github.com/pluskid/Mocha.jl) * plot\_statistics.jl Reads snapshots-cpu/statistics.jld (created by Mocha) and displays data using PyCall. * see\_snapshots.jl Sample code for reading data in hdf5 files. ### Data * /data/test.txt pointer to tell mocha to use the \*.hdf5 files generated by the convert.jl script. * /data/train.txt pointer to data/train.hdf5 * /data/sampleSubmission.csv contains all the test image numbers (all A submission) * /data/juliaSubmission.csv latest submission using Mocha * /data/juliaKNNSubmission.csv submission from KNN script