Using MLflow on google colaboratory with github to build cosy environment: building

• template_with_mlflow

  1 2 0.0 PureBasic

  This is a template repository for building a model and managing the trials with google colaboratory, drive, and MLflow.

github repository: template_with_mlflow

• Puts Debuggerer

  3,152 91 5.5 Ruby

  Ruby library for improved puts debugging, automatically displaying bonus useful information such as source line number and source code.

# Mount your google drive from google.colab import drive drive_path = "/content/gdrive" drive.mount(drive_path) # Load git settings and set the config with open(os.path.join(drive_path, "MyDrive", "settings", "github.txt"), "r") as f: mail = f.readline().replace("\n", "") user_name = f.readline().replace("\n", "") token = f.readline().replace("\n", "") !git config --global user.email {mail} !git config --global user.name {user_name} # Clone the repository repository_name = "template_with_mlflow" git_repository = f"https://github.com/{user_name}/" + repository_name + ".git" repository_path = "/content/" + repository_name !git clone {git_repository} # Change directory to the cloned directory %cd template_with_mlflow # Checkout branch_name = "develop" !git checkout {branch_name} # Pull !git pull

• WorkOS

  workos.com sponsored

  The modern identity platform for B2B SaaS. The APIs are flexible and easy-to-use, supporting authentication, user identity, and complex enterprise features like SSO and SCIM provisioning.

  

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