Open-Source CI/CD platform for ML teams. Deliver ML products, better & faster. ⚡️🧑‍🔧

Overview

giskardlogo

Deliver ML products, better & faster


Giskard is an Open-Source CI/CD platform for ML teams.

  • Inspect ML models visually from your Python notebook 📗
  • Review ML models collaboratively to get feedback on potential errors 🧐
  • Test ML models automatically for a safe deployment to production

Administration panel


Installation

git clone https://github.com/Giskard-AI/giskard.git
cd giskard
docker-compose up -d

After the application is started you can access at:

http://localhost:19000

login / password: admin / admin

Requirements

Quick Start

You can upload models to Giskard from Jupyter notebooks or any other python environment. it can be done using Giskard client library

There's a demo python notebook available at http://localhost:18888 that can be used to upload a first model.

Documentation

Find out more about Giskard by reading our docs

Community

Join our community on Discord to get support and leave feedback

Comments
  • project key : fix incompatible check with generated key from project name

    project key : fix incompatible check with generated key from project name

    Description

    Change validation pattern to comply with the automatic generated key.

    Related Issue

    Closes #96

    Type of Change

    • [ ] 📚 Examples / docs / tutorials / dependencies update
    • [x] 🔧 Bug fix (non-breaking change which fixes an issue)
    • [ ] 🥂 Improvement (non-breaking change which improves an existing feature)
    • [ ] 🚀 New feature (non-breaking change which adds functionality)
    • [ ] 💥 Breaking change (fix or feature that would cause existing functionality to change)
    • [ ] 🔐 Security fix

    Checklist

    • [x] I've read the CODE_OF_CONDUCT.md document.
    • [x] I've read the CONTRIBUTING.md guide.
    • [x] I've updated the code style using make codestyle.
    • [x] I've written tests for all new methods and classes that I created.
    • [x] I've written the docstring in Google format for all the methods and classes that I used.
    opened by lodovicoazzini 6
  • Add progress information on inspection loading modal

    Add progress information on inspection loading modal

    This step is often taking over 30 seconds. With a simple spinner and no information on the progress, it leads the user to wonder if there is not a bug.

    It would be a much better UX to have a % progress information

    CleanShot 2022-12-13 at 15 04 28@2x enhancement 
    opened by alexcombessie 5
  • File not found

    File not found

    The PFA file Worker is not found. And the said folder contains various errors when opened in my IDE.

    https://github.com/Giskard-AI/giskard/blob/92d1deb14bbe47a7df222def72d5297ce0cbb50f/giskard-server/src/main/java/ai/giskard/ml/MLWorkerClient.java#L10

    Screenshot from 2022-09-27 23-23-11

    opened by p4puniya 5
  • Overview always has a teal color even when it's not selected #610

    Overview always has a teal color even when it's not selected #610

    Description

    Related Issue

    Type of Change

    • [ ] 📚 Examples / docs / tutorials / dependencies update
    • [x] 🔧 Bug fix (non-breaking change which fixes an issue)
    • [x] 🥂 Improvement (non-breaking change which improves an existing feature)
    • [ ] 🚀 New feature (non-breaking change which adds functionality)
    • [ ] 💥 Breaking change (fix or feature that would cause existing functionality to change)
    • [ ] 🔐 Security fix

    Checklist

    • [ ] I've read the CODE_OF_CONDUCT.md document.
    • [ ] I've read the CONTRIBUTING.md guide.
    • [ ] I've updated the code style using make codestyle.
    • [ ] I've written tests for all new methods and classes that I created.
    • [ ] I've written the docstring in Google format for all the methods and classes that I used.
    opened by p4puniya 4
  • #387 - Make LIME categories searchable

    #387 - Make LIME categories searchable

    Description

    • [x] Convert <v-select> to <v-autocomplete> to add simple search to LIME Categories
    • [x] Migrate TeamExplanation.vue to use the Composition API
    • [x] Add a small doc to help with component migration in the future

    Related Issue

    #387 #432 => Tick TeamExplanation.vue when merged

    Type of Change

    • [x] 📚 Examples / docs / tutorials / dependencies update
    • [ ] 🔧 Bug fix (non-breaking change which fixes an issue)
    • [x] 🥂 Improvement (non-breaking change which improves an existing feature)
    • [ ] 🚀 New feature (non-breaking change which adds functionality)
    • [ ] 💥 Breaking change (fix or feature that would cause existing functionality to change)
    • [ ] 🔐 Security fix
    opened by Googleton 4
  • CGI -- problem with custom filtering

    CGI -- problem with custom filtering

    GSK-348

    When selecting the custom filter, and setting:

    • Actual labels = 0
    • Predicted labels = 1

    one of the data entries shown has:

    • Actual labels = 0
    • Predicted labels = 0

    Upon investigation, when we click on Model --> Inspect (i.e. the inspection is done for the whole dataset) this is the data entry in question:

    ,ETAB_ACT_DATE_DEBUT_ACTIVITE,ETAB_ACT_MODALITE_EXERCICE,GEST_MAJ_DATE,GDP_FLAG_RGE,ENT_ACT_DATE_IMMAT_RM,ENT_ACT_NON_SEDENTAIRE,ENT_GEST_MAJ_DATE,ENT_GEST_NON_DIFFUSION,DIR_ID_NATIONALITE,DIR_ID_DATE_NAISSANCE,DIR_ID_LISTE_DIFFUSION,DIR_ID_DATE_DEBUT_ACTIVITE,DIR_ADR_PAYS,DIR_FOR_FORAIN,DIR_QA_QUALIFICATION,DIR_QA_DATE,DIR_GEST_MAJ_DATE,INTITULE_ORIGINE_ETABLISSEMENT,INTITULE_CATEGORIE_ETABLISSEMENT,ETAB_NON_SEDENTAIRE,ETAB_AUDIT,DIR_CC_PRESENT,DIR_NATION,TYPOLOGIE_URBAIN_RURAL,ENT_ACT_FORME_JURIDIQUE_2
    54,13.971252566735114,Permanente,7.468856947296373,0,13.943874058863791,0,7.468856947296373,False,050,70.48596851471595,0,13.971252566735114,FRANCE,0,SANS QUALIFICATION,121.84804928131418,7.468856947296373,Création,Siège et établissement principal,0,1,0,Fr,urbain densité intermédiaire,54,0
    

    and the prediction (for labels [0, 1]) is:

    0.49382649000731726,0.5061735099926827
    

    -------------

    Now when skimming through the data, i.e. running prediction only on this entry, this is the resulting prediction (for labels [0, 1]) instead is:

    0.72773,0.27227
    

    so completely different predictions.

    Project: Giskard Reporter: rabah Created: 2022-11-09

    bug yt p:critical yt_client:cgi 
    opened by andreybavt 4
  • Update to readme.md

    Update to readme.md

    Description

    Related Issue

    Type of Change

    • [x] 📚 Examples / docs / tutorials / dependencies update
    • [ ] 🔧 Bug fix (non-breaking change which fixes an issue)
    • [ ] 🥂 Improvement (non-breaking change which improves an existing feature)
    • [ ] 🚀 New feature (non-breaking change which adds functionality)
    • [ ] 💥 Breaking change (fix or feature that would cause existing functionality to change)
    • [ ] 🔐 Security fix

    Checklist

    • [x] I've read the CODE_OF_CONDUCT.md document.
    • [x] I've read the CONTRIBUTING.md guide.
    • [x] I've updated the code style using make codestyle.
    • [x] I've written tests for all new methods and classes that I created.
    • [x] I've written the docstring in Google format for all the methods and classes that I used.
    opened by mackerac 4
  • Bump async from 2.6.3 to 2.6.4 in /frontend

    Bump async from 2.6.3 to 2.6.4 in /frontend

    Bumps async from 2.6.3 to 2.6.4.

    Changelog

    Sourced from async's changelog.

    v2.6.4

    • Fix potential prototype pollution exploit (#1828)
    Commits
    Maintainer changes

    This version was pushed to npm by hargasinski, a new releaser for async since your current version.


    Dependabot compatibility score

    Dependabot will resolve any conflicts with this PR as long as you don't alter it yourself. You can also trigger a rebase manually by commenting @dependabot rebase.


    Dependabot commands and options

    You can trigger Dependabot actions by commenting on this PR:

    • @dependabot rebase will rebase this PR
    • @dependabot recreate will recreate this PR, overwriting any edits that have been made to it
    • @dependabot merge will merge this PR after your CI passes on it
    • @dependabot squash and merge will squash and merge this PR after your CI passes on it
    • @dependabot cancel merge will cancel a previously requested merge and block automerging
    • @dependabot reopen will reopen this PR if it is closed
    • @dependabot close will close this PR and stop Dependabot recreating it. You can achieve the same result by closing it manually
    • @dependabot ignore this major version will close this PR and stop Dependabot creating any more for this major version (unless you reopen the PR or upgrade to it yourself)
    • @dependabot ignore this minor version will close this PR and stop Dependabot creating any more for this minor version (unless you reopen the PR or upgrade to it yourself)
    • @dependabot ignore this dependency will close this PR and stop Dependabot creating any more for this dependency (unless you reopen the PR or upgrade to it yourself) You can disable automated security fix PRs for this repo from the Security Alerts page.
    dependencies javascript 
    opened by dependabot[bot] 4
  • #597 - Change loading to indefinite progress bar for Inspector Launcher

    #597 - Change loading to indefinite progress bar for Inspector Launcher

    Description

    • [x] Change loading from spinner to indefinite progress bar
    • [x] Migrate InspectorLauncher.vue to Composition API

    Related Issue

    #432 => InspectorLauncher.vue migrated

    opened by Googleton 3
  • Gsk-395 removed httpretty from poetry

    Gsk-395 removed httpretty from poetry

    Description

    removed httpretty package from poetry requirements

    Related Issue

    https://giskard.youtrack.cloud/agiles/121-12/current?issue=GSK-395

    Type of Change

    • [ ] 📚 Examples / docs / tutorials / dependencies update
    • [ ] 🔧 Bug fix (non-breaking change which fixes an issue)
    • [x] 🥂 Improvement (non-breaking change which improves an existing feature)
    • [ ] 🚀 New feature (non-breaking change which adds functionality)
    • [ ] 💥 Breaking change (fix or feature that would cause existing functionality to change)
    • [ ] 🔐 Security fix
    opened by rabah-khalek 3
  • Refine devcontainer configuration with gradle

    Refine devcontainer configuration with gradle

    Description

    Related Issue

    Type of Change

    • [ ] 📚 Examples / docs / tutorials / dependencies update
    • [ ] 🔧 Bug fix (non-breaking change which fixes an issue)
    • [x] 🥂 Improvement (non-breaking change which improves an existing feature)
    • [ ] 🚀 New feature (non-breaking change which adds functionality)
    • [ ] 💥 Breaking change (fix or feature that would cause existing functionality to change)
    • [ ] 🔐 Security fix

    Checklist

    • [x] I've read the CODE_OF_CONDUCT.md document.
    • [x] I've read the CONTRIBUTING.md guide.
    • [ ] I've updated the code style using make codestyle.
    • [ ] I've written tests for all new methods and classes that I created.
    • [ ] I've written the docstring in Google format for all the methods and classes that I used.
    opened by alexcombessie 3
  • 497 need to be able to rename datasets and models from the UI

    497 need to be able to rename datasets and models from the UI

    Description

    Added the possibility to rename dataset and models for admin and project owner

    Related Issue

    Migration of component (https://github.com/Giskard-AI/giskard/issues/432):

    • Models.vue
    • Datasets.vue

    Type of Change

    • [ ] 📚 Examples / docs / tutorials / dependencies update
    • [ ] 🔧 Bug fix (non-breaking change which fixes an issue)
    • [x] 🥂 Improvement (non-breaking change which improves an existing feature)
    • [x] 🚀 New feature (non-breaking change which adds functionality)
    • [ ] 💥 Breaking change (fix or feature that would cause existing functionality to change)
    • [ ] 🔐 Security fix

    Checklist

    • [x] I've read the CODE_OF_CONDUCT.md document.
    • [x] I've read the CONTRIBUTING.md guide.
    • [ ] I've updated the code style using make codestyle.
    • [ ] I've written tests for all new methods and classes that I created.
    • [ ] I've written the docstring in Google format for all the methods and classes that I used.
    opened by kevinmessiaen 1
  • 487 option to delete feedbacks

    487 option to delete feedbacks

    Description

    Added possibility to delete feedback in the feedbacks list view

    Related Issue

    N/A

    Type of Change

    • [ ] 📚 Examples / docs / tutorials / dependencies update
    • [ ] 🔧 Bug fix (non-breaking change which fixes an issue)
    • [x] 🥂 Improvement (non-breaking change which improves an existing feature)
    • [ ] 🚀 New feature (non-breaking change which adds functionality)
    • [ ] 💥 Breaking change (fix or feature that would cause existing functionality to change)
    • [ ] 🔐 Security fix

    Checklist

    • [x] I've read the CODE_OF_CONDUCT.md document.
    • [x] I've read the CONTRIBUTING.md guide.
    • [ ] I've updated the code style using make codestyle.
    • [ ] I've written tests for all new methods and classes that I created.
    • [ ] I've written the docstring in Google format for all the methods and classes that I used.
    opened by kevinmessiaen 1
  • Blank screen on saving test suits without any changes

    Blank screen on saving test suits without any changes

    🐛 Bug Report

    The settings button shows a blank screen if we save the test suit settings without making any changes.

    🔬 How To Reproduce

    Steps to reproduce the behavior:

    1. Create a test suit however u like.
    2. Click on the settings/Edit button and save it without making any changes.
    3. Now, if you click the settings button again, it'll show a blank Screen

    Screenshots

    This is the output after Step-3

    image

    📈 Expected behavior

    The settings menu should be shown when the button is clicked.

    image

    bug 
    opened by p4puniya 0
  • Remove user access management from open source version

    Remove user access management from open source version

    Description

    • [x] Migrate Vuex => Pinia
    • [ ] Add proper feature management
    • [x] Rework the settings view to better split between user settings and general settings
    • [ ] Make the frontend use feature flags to hide user management entirely

    Related Issue

    #614 #432 ==> Components Migrated:

    • PasswordRecovery.vue
    • ResetPassword.vue
    • Signup.vue
    • Dashboard.vue
    • AdminUsers.vue
    • CreateUser.vue
    • EditUser.vue
    • InviteUsers.vue
    • UserProfile.vue
    • UserProfileEditPassword.vue
    • Project.vue

    Type of Change

    • [ ] 📚 Examples / docs / tutorials / dependencies update
    • [ ] 🔧 Bug fix (non-breaking change which fixes an issue)
    • [x] 🥂 Improvement (non-breaking change which improves an existing feature)
    • [x] 🚀 New feature (non-breaking change which adds functionality)
    • [ ] 💥 Breaking change (fix or feature that would cause existing functionality to change)
    • [ ] 🔐 Security fix
    opened by Googleton 1
  • Class based model/dataset upload based on MLFlow

    Class based model/dataset upload based on MLFlow

    An example of a new API:

    Changes implemented in this PR are not backward compatible with the old datasets/models since the storage format has changed

    from giskard import Model, SKLearnModel, GiskardClient, Dataset
    from giskard.core.core import SupportedModelTypes
    
    clf = ...  # regular model (scikit-learn for example)
    df = ...  # pandas dataframe
    
    
    def my_data_preparation_pipeline(df):
        return df
    
    
    model = SKLearnModel(model=clf,
                         model_type=SupportedModelTypes.CLASSIFICATION,
                         data_preparation_function=my_data_preparation_pipeline,
                         )
    dataset = Dataset(df, name="My Dataset", target="survived")
    
    client = GiskardClient("http://localhost:9000", "API_KEY")
    
    # save model and dataset to Giskard server
    mid = model.save(client, "project_key", validate_ds=dataset)
    did = dataset.save(client, "project_key")
    
    # load model and dataset from Giskard server
    model = Model.load(client, "project_key", mid)
    dataset = Model.load(client, "project_key", did)
    

    Internal artifact storage in GISKARD_HOME:

    ~/giskard-home/projects/mlflow
    ├── datasets
    │   ├── 00c4cf2f1b22404ba5003e2a924ec105
    │   │   ├── data.csv.zst
    │   │   └── giskard-dataset-meta.yaml
    │   └── ff71d57ec278435caf3d31d73c29c3e4
    │       ├── data.csv.zst
    │       └── giskard-dataset-meta.yaml
    └── models
        └── 0c003c62cbe14913a7997887ec1d6a21
            ├── MLmodel
            ├── conda.yaml
            ├── giskard-data-prep.pkl
            ├── giskard-model-meta.yaml
            ├── model.pkl
            ├── python_env.yaml
            └── requirements.txt
    
    • [x] migrated from -h,-p worker cli params to -u and -k for giskard server URL and API Key
    • [x] implement Model and Dataset save/load API methods
    • [x] fix artifact download from the UI
    • [ ] adapt demo projects to the new artifact storage
    • [x] fix internal ML Worker startup to work without client
    new-upload-api 
    opened by andreybavt 1
Releases(v1.3.0)
  • v1.3.0(Nov 23, 2022)

    External ML Worker - a new way to execute models 🐍

    This new feature allows reusing existing Python code environments when executing models. No need to re-create new environments with the same packages as at the model creation time. It requires giskard python package of version 1.7.0 more information is available in the documentation

    Other changes 📜

    • API for test execution
    • Disparate impact test
    • Improved test UI
    • Improved Inspection UI for classification models
    • Better example notebooks
    • Better support for large models
    • Customisable number of Lime samples
    • arm64 docker images

    New Contributors 👋

    • @thomasabou01
    • @rabah-khalek

    Full Changelog: https://github.com/Giskard-AI/giskard/compare/v1.2.0...v1.3.0

    Source code(tar.gz)
    Source code(zip)
  • v1.2.0(Sep 2, 2022)

    What's Changed

    • Configure devcontainer for codespaces setup by @alexcombessie in https://github.com/Giskard-AI/giskard/pull/119
    • Bump jackson-dataformat-yaml from 2.13.2 to 2.13.3 in /giskard-server by @dependabot in https://github.com/Giskard-AI/giskard/pull/108
    • Bump springdoc-openapi-ui from 1.6.7 to 1.6.9 in /giskard-server by @dependabot in https://github.com/Giskard-AI/giskard/pull/106
    • Bump com.google.cloud.tools.jib from 3.2.0 to 3.2.1 in /giskard-server by @dependabot in https://github.com/Giskard-AI/giskard/pull/107
    • Bump zstd-jni from 1.5.2-2 to 1.5.2-3 in /giskard-server by @dependabot in https://github.com/Giskard-AI/giskard/pull/110
    • Bump great-expectations from 0.15.8 to 0.15.11 in /giskard-ml-worker by @dependabot in https://github.com/Giskard-AI/giskard/pull/118
    • Bump grpcio from 1.46.3 to 1.47.0 in /giskard-ml-worker by @dependabot in https://github.com/Giskard-AI/giskard/pull/117
    • GSK-138: Delete labels in inspection by @qgk75 in https://github.com/Giskard-AI/giskard/pull/90
    • added mixpanel analytics collection by @andreybavt in https://github.com/Giskard-AI/giskard/pull/127
    • Update favicon by @alexcombessie in https://github.com/Giskard-AI/giskard/pull/130
    • GSK-184 Giskard client: drop target variable from df by @andreybavt in https://github.com/Giskard-AI/giskard/pull/136
    • Create CONTRIBUTING.md by @jmsquare in https://github.com/Giskard-AI/giskard/pull/129
    • GSK-162: Make the error message more explicit by @jmsquare in https://github.com/Giskard-AI/giskard/pull/154
    • Threshold for performance test for regression by @jmsquare in https://github.com/Giskard-AI/giskard/pull/153
    • show API token expiry date by @andreybavt in https://github.com/Giskard-AI/giskard/pull/155
    • Task/gsk 187 add link to upload UI by @alexcombessie in https://github.com/Giskard-AI/giskard/pull/156
    • skip sonar for dependabot by @andreybavt in https://github.com/Giskard-AI/giskard/pull/159
    • Bump moment from 2.29.3 to 2.29.4 in /giskard-frontend by @dependabot in https://github.com/Giskard-AI/giskard/pull/160
    • Sort SHAP explanation charts by @alexcombessie in https://github.com/Giskard-AI/giskard/pull/144
    • Bump great-expectations from 0.15.11 to 0.15.14 in /giskard-ml-worker by @dependabot in https://github.com/Giskard-AI/giskard/pull/168
    • Bump io.freefair.lombok from 6.4.1 to 6.5.0.3 in /giskard-server by @dependabot in https://github.com/Giskard-AI/giskard/pull/167
    • Bump @vue/cli-service from 5.0.4 to 5.0.8 in /giskard-frontend by @dependabot in https://github.com/Giskard-AI/giskard/pull/162
    • Bump vuetify from 2.6.6 to 2.6.7 in /giskard-frontend by @dependabot in https://github.com/Giskard-AI/giskard/pull/166
    • Bump vue-echarts from 6.0.3 to 6.2.3 in /giskard-frontend by @dependabot in https://github.com/Giskard-AI/giskard/pull/163
    • Bump eslint from 8.17.0 to 8.20.0 in /giskard-frontend by @dependabot in https://github.com/Giskard-AI/giskard/pull/165
    • GSK-190 added updated files from previous branch by @princyiakov in https://github.com/Giskard-AI/giskard/pull/169
    • GSK-166 Custom filtering for regression is not working by @andreybavt in https://github.com/Giskard-AI/giskard/pull/171
    • AWS AMI creation by @reneab in https://github.com/Giskard-AI/giskard/pull/161
    • Bump terser from 5.14.0 to 5.14.2 in /giskard-frontend by @dependabot in https://github.com/Giskard-AI/giskard/pull/170
    • Bump @vue/cli-plugin-typescript from 5.0.4 to 5.0.8 in /giskard-frontend by @dependabot in https://github.com/Giskard-AI/giskard/pull/174
    • Bump great-expectations from 0.15.14 to 0.15.15 in /giskard-ml-worker by @dependabot in https://github.com/Giskard-AI/giskard/pull/179
    • Gsk 205 metamorphic test for categorical perturbation is not working by @princyiakov in https://github.com/Giskard-AI/giskard/pull/181
    • GSK-214 sample custom test by @princyiakov in https://github.com/Giskard-AI/giskard/pull/182
    • Bump @sentry/types from 7.1.0 to 7.7.0 in /giskard-frontend by @dependabot in https://github.com/Giskard-AI/giskard/pull/180
    • Bump date-fns from 2.28.0 to 2.29.1 in /giskard-frontend by @dependabot in https://github.com/Giskard-AI/giskard/pull/176
    • Bump @typescript-eslint/eslint-plugin from 5.27.1 to 5.31.0 in /giskard-frontend by @dependabot in https://github.com/Giskard-AI/giskard/pull/177
    • Gsk 206 refactor demo projects by @princyiakov in https://github.com/Giskard-AI/giskard/pull/173
    • Delete LICENSE by @andreybavt in https://github.com/Giskard-AI/giskard/pull/185
    • Script and service for AMI creation by @reneab in https://github.com/Giskard-AI/giskard/pull/184
    • Add project key display on projects page by @alexcombessie in https://github.com/Giskard-AI/giskard/pull/188
    • Remove dataset ui upload by @alexcombessie in https://github.com/Giskard-AI/giskard/pull/187
    • Bump vuetify from 2.6.7 to 2.6.8 in /giskard-frontend by @dependabot in https://github.com/Giskard-AI/giskard/pull/190
    • Bump vue and vue-template-compiler in /giskard-frontend by @dependabot in https://github.com/Giskard-AI/giskard/pull/191
    • Bump sass from 1.52.2 to 1.54.0 in /giskard-frontend by @dependabot in https://github.com/Giskard-AI/giskard/pull/192
    • Bump @fortawesome/vue-fontawesome from 2.0.6 to 2.0.8 in /giskard-frontend by @dependabot in https://github.com/Giskard-AI/giskard/pull/193
    • GSK-206 fix pytorch model by @princyiakov in https://github.com/Giskard-AI/giskard/pull/186
    • GSK-232 target column not available validation added for performance … by @princyiakov in https://github.com/Giskard-AI/giskard/pull/194
    • Bump @fortawesome/fontawesome-svg-core from 6.1.1 to 6.1.2 in /giskard-frontend by @dependabot in https://github.com/Giskard-AI/giskard/pull/198
    • Bump eslint from 8.20.0 to 8.21.0 in /giskard-frontend by @dependabot in https://github.com/Giskard-AI/giskard/pull/199
    • Bump @types/node from 17.0.41 to 18.6.5 in /giskard-frontend by @dependabot in https://github.com/Giskard-AI/giskard/pull/196
    • Bump vuetify-loader from 1.7.3 to 1.9.2 in /giskard-frontend by @dependabot in https://github.com/Giskard-AI/giskard/pull/197
    • Bump great-expectations from 0.15.16 to 0.15.17 in /giskard-ml-worker by @dependabot in https://github.com/Giskard-AI/giskard/pull/202
    • Bump core-js from 3.22.8 to 3.24.1 in /giskard-frontend by @dependabot in https://github.com/Giskard-AI/giskard/pull/200
    • Disable SHAP for a single feature by @alexcombessie in https://github.com/Giskard-AI/giskard/pull/204
    • Bump pydantic from 1.9.1 to 1.9.2 in /giskard-ml-worker by @dependabot in https://github.com/Giskard-AI/giskard/pull/214
    • Bump echarts from 5.3.2 to 5.3.3 in /giskard-frontend by @dependabot in https://github.com/Giskard-AI/giskard/pull/207
    • Bump sass from 1.54.0 to 1.54.4 in /giskard-frontend by @dependabot in https://github.com/Giskard-AI/giskard/pull/209
    • Bump springdoc-openapi-ui from 1.6.9 to 1.6.10 in /giskard-server by @dependabot in https://github.com/Giskard-AI/giskard/pull/210
    • Bump typescript from 4.7.3 to 4.7.4 in /giskard-frontend by @dependabot in https://github.com/Giskard-AI/giskard/pull/212
    • Bump nbconvert from 5.5.0 to 6.3.0 in /giskard-ml-worker by @dependabot in https://github.com/Giskard-AI/giskard/pull/205
    • Bug/gsk 212 demo notebook bug shapley doesn't work for pytorch model by @princyiakov in https://github.com/Giskard-AI/giskard/pull/206
    • Bump mistune from 0.8.4 to 2.0.3 in /giskard-ml-worker by @dependabot in https://github.com/Giskard-AI/giskard/pull/215
    • replace nan values in dataset before writing CSV by @andreybavt in https://github.com/Giskard-AI/giskard/pull/225
    • Gsk 234 improve current tests by @princyiakov in https://github.com/Giskard-AI/giskard/pull/195
    • Bug/gsk 254 auc test throws error for multiclass model with small dataset by @princyiakov in https://github.com/Giskard-AI/giskard/pull/230

    New Contributors

    • @jmsquare made their first contribution in https://github.com/Giskard-AI/giskard/pull/129
    • @reneab made their first contribution in https://github.com/Giskard-AI/giskard/pull/161

    Full Changelog: https://github.com/Giskard-AI/giskard/compare/v1.1.0...v1.2.0

    Source code(tar.gz)
    Source code(zip)
  • v1.1.0(Jun 24, 2022)

  • v1.0.0(Jun 9, 2022)

  • v0.2.0(May 4, 2022)

  • v0.1.1(Apr 11, 2022)

Owner
Giskard
Deliver ML products, better & faster.
Giskard
Class-imbalanced / Long-tailed ensemble learning in Python. Modular, flexible, and extensible

IMBENS: Class-imbalanced Ensemble Learning in Python Language: English | Chinese/中文 Links: Documentation | Gallery | PyPI | Changelog | Source | Downl

Zhining Liu 176 Jan 04, 2023
Little Ball of Fur - A graph sampling extension library for NetworKit and NetworkX (CIKM 2020)

Little Ball of Fur is a graph sampling extension library for Python. Please look at the Documentation, relevant Paper, Promo video and External Resour

Benedek Rozemberczki 619 Dec 14, 2022
A simple application that calculates the probability distribution of a normal distribution

probability-density-function General info An application that calculates the probability density and cumulative distribution of a normal distribution

1 Oct 25, 2022
Continuously evaluated, functional, incremental, time-series forecasting

timemachines Autonomous, univariate, k-step ahead time-series forecasting functions assigned Elo ratings You can: Use some of the functionality of a s

Peter Cotton 343 Jan 04, 2023
End to End toy example of MLOps

churn_model MLOps Toy Example End to End You might find below links useful Connect VSCode to Git MLFlow Port Heroku App Project Organization ├── LICEN

Ashish Tele 6 Feb 06, 2022
使用数学和计算机知识投机倒把

偷鸡不成项目集锦 坦率地讲,涉及金融市场的好策略如果公开,必然导致使用的人多,最后策略变差。所以这个仓库只收集我目前失败了的案例。 加密货币组合套利 中国体育彩票预测 我赚不上钱的项目,也许可以帮助更有能力的人去赚钱。

Roy 28 Dec 29, 2022
QuickAI is a Python library that makes it extremely easy to experiment with state-of-the-art Machine Learning models.

QuickAI is a Python library that makes it extremely easy to experiment with state-of-the-art Machine Learning models.

152 Jan 02, 2023
MLR - Machine Learning Research

Machine Learning Research 1. Project Topic 1.1. Exsiting research Benmark: https://paperswithcode.com/sota ACL anthology for NLP papers: http://www.ac

Charles 69 Oct 20, 2022
We have a dataset of user performances. The project is to develop a machine learning model that will predict the salaries of baseball players.

Salary-Prediction-with-Machine-Learning 1. Business Problem Can a machine learning project be implemented to estimate the salaries of baseball players

Ayşe Nur Türkaslan 9 Oct 14, 2022
Implementations of Machine Learning models, Regularizers, Optimizers and different Cost functions.

Linear Models Implementations of LinearRegression, LassoRegression and RidgeRegression with appropriate Regularizers and Optimizers. Linear Regression

Keivan Ipchi Hagh 1 Nov 22, 2021
pywFM is a Python wrapper for Steffen Rendle's factorization machines library libFM

pywFM pywFM is a Python wrapper for Steffen Rendle's libFM. libFM is a Factorization Machine library: Factorization machines (FM) are a generic approa

João Ferreira Loff 251 Sep 23, 2022
Distributed training framework for TensorFlow, Keras, PyTorch, and Apache MXNet.

Horovod Horovod is a distributed deep learning training framework for TensorFlow, Keras, PyTorch, and Apache MXNet. The goal of Horovod is to make dis

Horovod 12.9k Jan 07, 2023
TensorFlow Decision Forests (TF-DF) is a collection of state-of-the-art algorithms for the training, serving and interpretation of Decision Forest models.

TensorFlow Decision Forests (TF-DF) is a collection of state-of-the-art algorithms for the training, serving and interpretation of Decision Forest models. The library is a collection of Keras models

538 Jan 01, 2023
虚拟货币(BTC、ETH)炒币量化系统项目。在一版本的基础上加入了趋势判断

🎉 第二版本 🎉 (现货趋势网格) 介绍 在第一版本的基础上 趋势判断,不在固定点位开单,选择更优的开仓点位 优势: 🎉 简单易上手 安全(不用将api_secret告诉他人) 如何启动 修改app目录下的authorization文件

幸福村的码农 250 Jan 07, 2023
Pyomo is an object-oriented algebraic modeling language in Python for structured optimization problems.

Pyomo is a Python-based open-source software package that supports a diverse set of optimization capabilities for formulating and analyzing optimization models. Pyomo can be used to define symbolic p

Pyomo 1.4k Dec 28, 2022
Arquivos do curso online sobre a estatística voltada para ciência de dados e aprendizado de máquina.

Estatistica para Ciência de Dados e Machine Learning Arquivos do curso online sobre a estatística voltada para ciência de dados e aprendizado de máqui

Renan Barbosa 1 Jan 10, 2022
A visual dataflow programming language for sklearn

Persimmon What is it? Persimmon is a visual dataflow language for creating sklearn pipelines. It represents functions as blocks, inputs and outputs ar

Álvaro Bermejo 194 Jan 04, 2023
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
Iris-Heroku - Putting a Machine Learning Model into Production with Flask and Heroku

Puesta en Producción de un modelo de aprendizaje automático con Flask y Heroku L

Jesùs Guillen 1 Jun 03, 2022
A simple and lightweight genetic algorithm for optimization of any machine learning model

geneticml This package contains a simple and lightweight genetic algorithm for optimization of any machine learning model. Installation Use pip to ins

Allan Barcelos 8 Aug 10, 2022