Tools for Optuna, MLflow and the integration of both.

Overview

HPOflow - Sphinx DOC

DOC MIT License Contributor Covenant Python Version pypi
pytest status Static Code Checks status Build & Deploy Doc GitHub issues

Tools for Optuna, MLflow and the integration of both.

Detailed documentation with examples can be found here: Sphinx DOC

Table of Contents

Maintainers

One Conversation
This project is maintained by the One Conversation team of Deutsche Telekom AG.

The main components are:

Installation

HPOflow is available at the Python Package Index (PyPI). It can be installed with pip:

$ pip install hpoflow

Some additional dependencies might be necessary.

To use hpoflow.optuna_mlflow.OptunaMLflow:

$ pip install mlflow GitPython

To use hpoflow.optuna_transformers.OptunaMLflowCallback:

$ pip install mlflow GitPython transformers

To install all optional dependencies use:

$ pip install hpoflow[optional]

Support and Feedback

The following channels are available for discussions, feedback, and support requests:

Reporting Security Vulnerabilities

This project is built with security and data privacy in mind to ensure your data is safe. We are grateful for security researchers and users reporting a vulnerability to us, first. To ensure that your request is handled in a timely manner and non-disclosure of vulnerabilities can be assured, please follow the below guideline.

Please do not report security vulnerabilities directly on GitHub. GitHub Issues can be publicly seen and therefore would result in a direct disclosure.

Please address questions about data privacy, security concepts, and other media requests to the [email protected] mailbox.

Contribution

Our commitment to open source means that we are enabling - in fact encouraging - all interested parties to contribute and become part of our developer community.

Contribution and feedback is encouraged and always welcome. For more information about how to contribute, as well as additional contribution information, see our Contribution Guidelines.

Code of Conduct

This project has adopted the Contributor Covenant as our code of conduct. Please see the details in our Contributor Covenant Code of Conduct. All contributors must abide by the code of conduct.

Licensing

Copyright (c) 2021 Philip May, Deutsche Telekom AG
Copyright (c) 2021 Philip May
Copyright (c) 2021 Timothy Wolff-Piggott

Licensed under the MIT License (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License by reviewing the file LICENSE in the repository.

Comments
  • review README.md and CONTRIBUTING.md

    review README.md and CONTRIBUTING.md

    Review README.md and CONTRIBUTING.md

    • is there something missing? maybe compare with optuna and transformers
    • spelling
    • idiomatic english
    • consistency
    • correctness
    • links ok?
    • ...

    PS: The real documentation is still missing and a know issue.

    opened by PhilipMay 12
  • add typing in optuna_transformers

    add typing in optuna_transformers

    @twolffpiggott can you please tell me the type of this?

    https://github.com/telekom/HPOflow/blob/e2b0943218af419a79ce95e60b67c9a4c2477349/hpoflow/optuna_transformers.py#L47

    opened by PhilipMay 6
  • add `transformers.py`

    add `transformers.py`

    @twolffpiggott should we add this here or to an other project we open source?

    https://github.com/PhilipMay/mltb/blob/master/mltb/integration/transformers.py

    enhancement 
    opened by PhilipMay 6
  • Create Sphinx documentation page

    Create Sphinx documentation page

    • [x] setup
    • [x] make GH action
    • [x] setup page
    • [x] change styling to telekom style
    • switch to MD
    • [x] add more content
    • [x] link from README to page
    • [x] link from pypi to GH page
    • [x] add impressum
    • [x] remove strange mouse over image effect
    • add version info
    documentation 
    opened by PhilipMay 4
  • Problems with direct `_imports.check()` call

    Problems with direct `_imports.check()` call

    When the __init__.py imports OMLflowCallback the optuna_transformers.py script is executed. That executes the _imports.check() call which then throws an exception if transformers or mlflow is not installed. But that should be avoided.

    See here: https://github.com/telekom/HPOflow/blob/d1cce5cbc2a84634d1484a053286000dda05b681/hpoflow/optuna_transformers.py#L11-L17

    The solution would be to put the _imports.check() call into the constructor. But that is not possible because OMLflowCallback inherits from transformers.

    The only solution I have is to put OMLflowCallback into an factory function that creates an OMLflowCallback and does the _imports.check() in there.

    @twolffpiggott what do you think?

    bug 
    opened by PhilipMay 3
  • Flake8 ignore list for Black compatibility

    Flake8 ignore list for Black compatibility

    Flake8 raises a warning for "E203" when it encounters a Black decision to insert whitespace before : in slicing syntax.

    Black's behaviour is more correct here, so my suggestion is to add "E203" to the flake8 config ignore list.

    i.e. in setup.cfg:

    [flake8]
    ...
    extend-ignore = E203
    opened by twolffpiggott 3
  • Simple Example?

    Simple Example?

    I don't understand how to use this package. Could you provide a basic example? I don't understand the import_structure and how it relates to importing the modules? Thanks

    opened by jmrichardson 2
  • WIP prefix in contrib file

    WIP prefix in contrib file

    Should this

    Create Work In Progress [WIP] pull requests only if you need clarification or an explicit review before you can continue your work item.

    be more like this

    Add a [WIP] prefix on your pull request name if you need clarification or an explicit review before you can continue your work item.

    documentation 
    opened by PhilipMay 2
Releases(0.1.4)
Owner
Telekom Open Source Software
published by Deutsche Telekom AG and partner companies
Telekom Open Source Software
A data preprocessing package for time series data. Design for machine learning and deep learning.

A data preprocessing package for time series data. Design for machine learning and deep learning.

Allen Chiang 152 Jan 07, 2023
A classification model capable of accurately predicting the price of secondhand cars

The purpose of this project is create a classification model capable of accurately predicting the price of secondhand cars. The data used for model building is open source and has been added to this

Akarsh Singh 2 Sep 13, 2022
UpliftML: A Python Package for Scalable Uplift Modeling

UpliftML is a Python package for scalable unconstrained and constrained uplift modeling from experimental data. To accommodate working with big data, the package uses PySpark and H2O models as base l

Booking.com 254 Dec 31, 2022
Microsoft Machine Learning for Apache Spark

Microsoft Machine Learning for Apache Spark MMLSpark is an ecosystem of tools aimed towards expanding the distributed computing framework Apache Spark

Microsoft Azure 3.9k Dec 30, 2022
LILLIE: Information Extraction and Database Integration Using Linguistics and Learning-Based Algorithms

LILLIE: Information Extraction and Database Integration Using Linguistics and Learning-Based Algorithms Based on the work by Smith et al. (2021) Query

5 Aug 06, 2022
AtsPy: Automated Time Series Models in Python (by @firmai)

Automated Time Series Models in Python (AtsPy) SSRN Report Easily develop state of the art time series models to forecast univariate data series. Simp

Derek Snow 465 Jan 02, 2023
An MLOps framework to package, deploy, monitor and manage thousands of production machine learning models

Seldon Core: Blazing Fast, Industry-Ready ML An open source platform to deploy your machine learning models on Kubernetes at massive scale. Overview S

Seldon 3.5k Jan 01, 2023
Machine Learning for Time-Series with Python.Published by Packt

Machine-Learning-for-Time-Series-with-Python Become proficient in deriving insights from time-series data and analyzing a model’s performance Links Am

Packt 124 Dec 28, 2022
Hierarchical Time Series Forecasting using Prophet

htsprophet Hierarchical Time Series Forecasting using Prophet Credit to Rob J. Hyndman and research partners as much of the code was developed with th

Collin Rooney 131 Dec 02, 2022
Lightweight Machine Learning Experiment Logging 📖

Simple logging of statistics, model checkpoints, plots and other objects for your Machine Learning Experiments (MLE). Furthermore, the MLELogger comes with smooth multi-seed result aggregation and co

Robert Lange 65 Dec 08, 2022
STUMPY is a powerful and scalable Python library for computing a Matrix Profile, which can be used for a variety of time series data mining tasks

STUMPY STUMPY is a powerful and scalable library that efficiently computes something called the matrix profile, which can be used for a variety of tim

TD Ameritrade 2.5k Jan 06, 2023
2D fluid simulation implementation of Jos Stam paper on real-time fuild dynamics, including some suggested extensions.

Fluid Simulation Usage Download this repo and store it in your computer. Open a terminal and go to the root directory of this folder. Make sure you ha

Mariana Ávalos Arce 5 Dec 02, 2022
Case studies with Bayesian methods

Case studies with Bayesian methods

Baze Petrushev 8 Nov 26, 2022
This is a curated list of medical data for machine learning

Medical Data for Machine Learning This is a curated list of medical data for machine learning. This list is provided for informational purposes only,

Andrew L. Beam 5.4k Dec 26, 2022
Fit interpretable models. Explain blackbox machine learning.

InterpretML - Alpha Release In the beginning machines learned in darkness, and data scientists struggled in the void to explain them. Let there be lig

InterpretML 5.2k Jan 09, 2023
Databricks Certified Associate Spark Developer preparation toolkit to setup single node Standalone Spark Cluster along with material in the form of Jupyter Notebooks.

Databricks Certification Spark Databricks Certified Associate Spark Developer preparation toolkit to setup single node Standalone Spark Cluster along

19 Dec 13, 2022
Retrieve annotated intron sequences and classify them as minor (U12-type) or major (U2-type)

(intron I nterrogator and C lassifier) intronIC is a program that can be used to classify intron sequences as minor (U12-type) or major (U2-type), usi

Graham Larue 4 Jul 26, 2022
Python 3.6+ toolbox for submitting jobs to Slurm

Submit it! What is submitit? Submitit is a lightweight tool for submitting Python functions for computation within a Slurm cluster. It basically wraps

Facebook Incubator 768 Jan 03, 2023
Uses WiFi signals :signal_strength: and machine learning to predict where you are

Uses WiFi signals and machine learning (sklearn's RandomForest) to predict where you are. Even works for small distances like 2-10 meters.

Pascal van Kooten 5k Jan 09, 2023
This is the material used in my free Persian course: Machine Learning with Python

This is the material used in my free Persian course: Machine Learning with Python

Yara Mohamadi 4 Aug 07, 2022