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IoT energy Efficiency Management Model Kit

by Mari Appan11

kandi

1-Click Install Available
(see Kit Deployment Instructions section below)

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.

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

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.

h2o-3by h2oai

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.

Jupyter Notebook Updated: 3 mo ago License: Permissive

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h2o-3by h2oai

Jupyter Notebook Updated: 3 mo ago License: Permissive

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.

Support
Quality
Security
License
Reuse

Kit Solution Source

https://github.com/dharneshk/sustainabiltyhackathon

Kit Deployment Instructions

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