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Sustainability hackathon kit

by Aryan Updated: Jan 9, 2022

We Aryan and Tejas of team VIT/OW/14 have built this kit that helps beginners and citizen data scientists to build machine learning models we hope u like it

OLAP data visualization

CBoardby TuiQiao

JavaScript star image 2910 Version:Current

License: Permissive (Apache-2.0)

An easy to use, self-service open BI reporting and BI dashboard platform.

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CBoardby TuiQiao

JavaScript star image 2910 Version:Current License: Permissive (Apache-2.0)

An easy to use, self-service open BI reporting and BI dashboard platform.
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grafanaby grafana

TypeScript star image 53647 Version:v8.5.16

License: Strong Copyleft (AGPL-3.0)

The open and composable observability and data visualization platform. Visualize metrics, logs, and traces from multiple sources like Prometheus, Loki, Elasticsearch, InfluxDB, Postgres and many more.

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grafanaby grafana

TypeScript star image 53647 Version:v8.5.16 License: Strong Copyleft (AGPL-3.0)

The open and composable observability and data visualization platform. Visualize metrics, logs, and traces from multiple sources like Prometheus, Loki, Elasticsearch, InfluxDB, Postgres and many more.
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Data Analysis

pandasby pandas-dev

Python star image 36688 Version:1.5.2

License: Permissive (BSD-3-Clause)

Flexible and powerful data analysis / manipulation library for Python, providing labeled data structures similar to R data.frame objects, statistical functions, and much more

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pandasby pandas-dev

Python star image 36688 Version:1.5.2 License: Permissive (BSD-3-Clause)

Flexible and powerful data analysis / manipulation library for Python, providing labeled data structures similar to R data.frame objects, statistical functions, and much more
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numpyby numpy

Python star image 22526 Version:1.24.1

License: Permissive (BSD-3-Clause)

The fundamental package for scientific computing with Python.

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numpyby numpy

Python star image 22526 Version:1.24.1 License: Permissive (BSD-3-Clause)

The fundamental package for scientific computing with Python.
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seabornby mwaskom

Python star image 10246 Version:0.12.2

License: Permissive (BSD-3-Clause)

Statistical data visualization in Python

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seabornby mwaskom

Python star image 10246 Version:0.12.2 License: Permissive (BSD-3-Clause)

Statistical data visualization in Python
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Data Labelling

label-studioby heartexlabs

Python star image 11794 Version:1.7.0

License: Permissive (Apache-2.0)

Label Studio is a multi-type data labeling and annotation tool with standardized output format

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label-studioby heartexlabs

Python star image 11794 Version:1.7.0 License: Permissive (Apache-2.0)

Label Studio is a multi-type data labeling and annotation tool with standardized output format
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VoTTby microsoft

TypeScript star image 3961 Version:v2.2.0

License: Permissive (MIT)

Visual Object Tagging Tool: An electron app for building end to end Object Detection Models from Images and Videos.

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VoTTby microsoft

TypeScript star image 3961 Version:v2.2.0 License: Permissive (MIT)

Visual Object Tagging Tool: An electron app for building end to end Object Detection Models from Images and Videos.
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cloud-annotationsby cloud-annotations

TypeScript star image 2653 Version:v1.3.2

License: Permissive (MIT)

🐝 A fast, easy and collaborative open source image annotation tool for teams and individuals.

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cloud-annotationsby cloud-annotations

TypeScript star image 2653 Version:v1.3.2 License: Permissive (MIT)

🐝 A fast, easy and collaborative open source image annotation tool for teams and individuals.
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labelboxby Labelbox

JavaScript star image 1686 Version:1

License: Permissive (Apache-2.0)

Labelbox is the fastest way to annotate data to build and ship computer vision applications.

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labelboxby Labelbox

JavaScript star image 1686 Version:1 License: Permissive (Apache-2.0)

Labelbox is the fastest way to annotate data to build and ship computer vision applications.
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Auto ML

ml-annotateby planbrothers

Python star image 79 Version:Current

License: Permissive (MIT)

Use ML-Annotate to label data for machine learning purposes

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ml-annotateby planbrothers

Python star image 79 Version:Current License: Permissive (MIT)

Use ML-Annotate to label data for machine learning purposes
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auto-sklearnby automl

Python star image 6704 Version:v0.14.7

License: Permissive (BSD-3-Clause)

Automated Machine Learning with scikit-learn

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auto-sklearnby automl

Python star image 6704 Version:v0.14.7 License: Permissive (BSD-3-Clause)

Automated Machine Learning with scikit-learn
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Auto-PyTorchby automl

Python star image 1899 Version:v0.2.1

License: Permissive (Apache-2.0)

Automatic architecture search and hyperparameter optimization for PyTorch

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Auto-PyTorchby automl

Python star image 1899 Version:v0.2.1 License: Permissive (Apache-2.0)

Automatic architecture search and hyperparameter optimization for PyTorch
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pycaretby pycaret

Jupyter Notebook star image 6839 Version:2.3.10

License: Permissive (MIT)

An open-source, low-code machine learning library in Python

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pycaretby pycaret

Jupyter Notebook star image 6839 Version:2.3.10 License: Permissive (MIT)

An open-source, low-code machine learning library in Python
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Kit Solution Source

automl-starterby kandikits

Jupyter Notebook star image 0 Version:Current

License: Permissive (MIT)

This repo helps beginners and citizen data scientists to build machine learning models

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automl-starterby kandikits

Jupyter Notebook star image 0 Version:Current License: Permissive (MIT)

This repo helps beginners and citizen data scientists to build machine learning models
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echartsby apache

TypeScript star image 53983 Version:5.4.1

License: Permissive (Apache-2.0)

Apache ECharts is a powerful, interactive charting and data visualization library for browser

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echartsby apache

TypeScript star image 53983 Version:5.4.1 License: Permissive (Apache-2.0)

Apache ECharts is a powerful, interactive charting and data visualization library for browser
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EarthHacksby byahya

JavaScript star image 1 Version:Current

License: No License (null)

site for sustainability hackathon

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EarthHacksby byahya

JavaScript star image 1 Version:Current License: No License

site for sustainability hackathon
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Deployment Information

This sections has the instructions to install the kit. For the Auto ML kit source, the deployment instructions are: 1. Clone the automl-starter from the source:https://github.com/Aryanodugoudar/sustainibility-hackathon 2. Install the required libraries by 'pip install -r requirements.txt' 3. Navigate to the 'automl-classification-pycaret.ipynb' and open and run each cells

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