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using DataFrames, Tables, CSV | |
using MLJ, MLJLinearModels, MLJBase | |
using Random: seed! | |
seed!(42); | |
train_df = CSV.File("train.csv"; threaded=true) |> DataFrame; | |
X_train = Matrix(train_df[!, names(train_df) .!== "Class"]) | |
y_train = categorical(train_df.Class) |
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❯ docker run -it 234 /bin/bash | |
(base) mambauser@e2183b470bad:/tmp$ micromamba install -y -n base -c conda-forge python=3.8 pip | |
__ | |
__ ______ ___ ____ _____ ___ / /_ ____ _ | |
/ / / / __ `__ \/ __ `/ __ `__ \/ __ \/ __ `/ | |
/ /_/ / / / / / / /_/ / / / / / / /_/ / /_/ / | |
/ .___/_/ /_/ /_/\__,_/_/ /_/ /_/_.___/\__,_/ | |
/_/ |
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#1 [internal] load build definition from Dockerfile2 | |
#1 sha256:cf89b44f159ea644e382c06606de4e903bb221caa3eacb56b12d80e31f358d9d | |
#1 transferring dockerfile: 39B done | |
#1 DONE 0.0s | |
#2 [internal] load .dockerignore | |
#2 sha256:be9e69f111131ade54e1e322c33ebcb02ced0969b71b6fff0875a786b3f50922 | |
#2 transferring context: 2B done | |
#2 DONE 0.0s |