MLDev. Experiment Reproducibility

This is the official documentation for the MLDev software. MLDev facilitates running data science experiments, help in results presentation and eases paper preparation for students, data scientists and researchers.

The MLDev software provides the following features to help with automating machine learning experiments:

• Configure stages and parameters of a data science experiment separately from your code

• Conduct a repeatable experiment in Google Colab or PaperSpace

• Keep versions of your code, results and intermediate files on Google Drive (other repos coming soon)

• Use a variety of pre-built templates to get started: see template-default and template-intelligent-systems

MLDev also provides some services that run alongside your experiment code:

• You can have the notifications via Telegram about the exeptions while training your model

• Keep updated on current experiment state using TensorBoard (even on Colab)

• Deploy and demo your model with a model controller (feature in progress)

Quick setup

MLDev is currently in Development stage.

Get the latest version of our install file to your local machine and run it.

$ curl https://gitlab.com/mlrep/mldev/-/raw/develop/install_mldev.sh -o install_mldev.sh
$ chmod +x ./install_mldev.sh
$ ./install_mldev.sh base

You may be asked for root privileges if there are system packages to be installed.

Wait a couple of minutes until installation will be done and then you are almost ready to use our instrument, congrats!

Then get the default demo experiment

$ mldev init <new_folder>

Answer the questions the setup wizard asks or skip where possible.

Then run the default pipeline of the experiment

$ cd <new_folder>
$ mldev run

User documentation

• A Quickstart Tutorial for MLDev
  • Contents
  • Installation instructions
  • Hello World!
  • Simple classification task on template-default
  • How to get help
• User Guide
  • Contents
  • Installation
  • Experiment setup
  • Running the experiment (locally)
  • Running the experiment (Google Colab)
  • Advanced usage

See more at the project Wiki

Developer docs

• Contribution Guidelines
  • General Guidelines
  • Pre-requisites
  • Translating and contributing docs and tutorials
  • Reporting bugs and code fixes
  • Joining the project
• MLDev Base
  • Experiments module
  • Experiment Tag module
  • Expressions module
  • Main module
  • Python context module
  • Execution utils module
  • Yaml Loader module
• MLDev Config Parser
  • Config parser module
• MLDev DVC integration
  • DVC integration module
• MLDev Jupyter integration
  • Jupyter integration module

Please check the CONTRIBUTING.md guide if you’d like to participate in the project, ask a question or give a suggestion.

Project sponsors and supporters

Contacts

Join the project Slack channel at #ml4sg.

You can reach developers at the Telegram user group

License

The software is licensed under Apache 2.0 license

Index and tables

• Index

• Module Index

• Search Page