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IoT energy Efficiency Management Model Kit

by Mari Appan11 Updated: Jan 9, 2022

Our solution uses Data Visualization to analyse the given data set using machine learning program to predict energy usage. This solution can be used to reduce the energy wastage during the manufacturing of IoT devices.

Data Visualization

We have clubbed these libraries for Data Visualization. we have used CBoard as a BI dashboard and grafana for Visual metrics and traces.

CBoardby TuiQiao

JavaScript star image 2708 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 2708 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 48159 Version:v8.5.0

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 48159 Version:v8.5.0 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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dablby dabl

Jupyter Notebook star image 621 Version:Current

License: Permissive (BSD-3-Clause)

Data Analysis Baseline Library

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dablby dabl

Jupyter Notebook star image 621 Version:Current License: Permissive (BSD-3-Clause)

Data Analysis Baseline Library
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Data analysis

data Analysis using dabl is a drop-in replacements for GridSearchCV and Randomized SearchCV using successive halfing. the pandas is flexible and manipulate the data set

pandasby pandas-dev

Python star image 33259 Version:v1.4.1

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 33259 Version:v1.4.1 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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universal-data-toolby UniversalDataTool

JavaScript star image 1429 Version:v0.14.26

License: Permissive (MIT)

Collaborate & label any type of data, images, text, or documents, in an easy web interface or desktop app.

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universal-data-toolby UniversalDataTool

JavaScript star image 1429 Version:v0.14.26 License: Permissive (MIT)

Collaborate & label any type of data, images, text, or documents, in an easy web interface or desktop app.
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cloud-annotationsby cloud-annotations

TypeScript star image 2616 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 2616 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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Data Labeling

we have clubbed the universal-data-tool and cloud-annotations for labelling the data in a proper format with open source image annotation tools and easy web interface or desktop app.

pycaretby pycaret

Jupyter Notebook star image 5481 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 5481 Version:2.3.10 License: Permissive (MIT)

An open-source, low-code machine learning library in Python
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h2o-3by h2oai

Jupyter Notebook star image 5797 Version:Current

License: Permissive (Apache-2.0)

H2O is an Open Source, Distributed, Fast & Scalable Machine Learning Platform: Deep Learning, Gradient Boosting (GBM) & XGBoost, Random Forest, Generalized Linear Modeling (GLM with Elastic Net), K-Means, PCA, Generalized Additive Models (GAM), RuleFit, Support Vector Machine (SVM), Stacked Ensembles, Automatic Machine Learning (AutoML), etc.

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h2o-3by h2oai

Jupyter Notebook star image 5797 Version:Current License: Permissive (Apache-2.0)

H2O is an Open Source, Distributed, Fast & Scalable Machine Learning Platform: Deep Learning, Gradient Boosting (GBM) & XGBoost, Random Forest, Generalized Linear Modeling (GLM with Elastic Net), K-Means, PCA, Generalized Additive Models (GAM), RuleFit, Support Vector Machine (SVM), Stacked Ensembles, Automatic Machine Learning (AutoML), etc.
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Sustainability hackathon

the solution for our sustainability hackathon

sustainabiltyhackathonby dharneshk

Jupyter Notebook star image 0 Version:Current

License: Permissive (MIT)

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sustainabiltyhackathonby dharneshk

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

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Deployment Information

https://github.com/dharneshk/sustainabiltyhackathon

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/dharneshk/sustainabiltyhackathon 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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