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irublev / gist:a347e00fc7f806d14b80849a37e7c59b
Created February 28, 2023 20:44
logs for Docker 20.10.23
#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
@irublev
irublev / gist:e3b0a7158dd3685364b701fab6d69474
Created February 28, 2023 17:58
logs for installing flakon via pip
❯ 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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/ / / / __ `__ \/ __ `/ __ `__ \/ __ \/ __ `/
/ /_/ / / / / / / /_/ / / / / / / /_/ / /_/ /
/ .___/_/ /_/ /_/\__,_/_/ /_/ /_/_.___/\__,_/
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@irublev
irublev / juliatestml.jl
Last active May 24, 2021 09:32
Comparison of ML in Julia (MLJ) and in Python (Scikit-learn)
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)