INTERNET OF THINGS AND ENERGY MANAGEMENT
by maniraj1192003 Updated: Jan 9, 2022
Solution Kit ย
THE GIVEN SOLUTITION USES DATA EXPLORATION TO CHECK DATA SET USING ADVANCE MACHINE LEARNING TO PREDICT THE ENERGY WASTEAGE
data visualization
CBoardby TuiQiao
An easy to use, self-service open BI reporting and BI dashboard platform.
CBoardby TuiQiao
JavaScript
2925
Version:Current
License: Permissive (Apache-2.0)
grafanaby grafana
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.
grafanaby grafana
TypeScript
54622
Version:v8.5.22
License: Strong Copyleft (AGPL-3.0)
data annalysize
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.
h2o-3by h2oai
Jupyter Notebook
6189
Version:Current
License: Permissive (Apache-2.0)
pycaretby pycaret
An open-source, low-code machine learning library in Python
pycaretby pycaret
Jupyter Notebook
7086
Version:3.0.0
License: Permissive (MIT)
pandasby pandas-dev
Flexible and powerful data analysis / manipulation library for Python, providing labeled data structures similar to R data.frame objects, statistical functions, and much more
pandasby pandas-dev
Python
37428
Version:v2.0.0rc1
License: Permissive (BSD-3-Clause)
data lable
label-studioby heartexlabs
Label Studio is a multi-type data labeling and annotation tool with standardized output format
label-studioby heartexlabs
Python
12415
Version:1.7.2
License: Permissive (Apache-2.0)
cloud-annotationsby cloud-annotations
๐ A fast, easy and collaborative open source image annotation tool for teams and individuals.
cloud-annotationsby cloud-annotations
TypeScript
2653
Version:v1.3.2
License: Permissive (MIT)
automl-starterby kandikits
This repo helps beginners and citizen data scientists to build machine learning models
automl-starterby kandikits
Jupyter Notebook
0
Version:Current
License: Permissive (MIT)
Deployment Information
1. Clone the automl-starter from the source: https://github.com/kandikits/automl-starter 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