By continuing you indicate that you have read and agree to our Terms of service and Privacy policy
Our solution uses AutoML to predict energy usage. This can be deployed for optimizing energy usage.
Data Exploration
We have created a group for the libraries used for Data Exploration in my solution. The data exploration helps in doing extensive analysis of different data types and in assisting to understand the patterns. Pandas is used in our solution for data manipulation and analysis.
CBoardby TuiQiao
JavaScript 2910 Version:Current
CBoardby TuiQiao
JavaScript 2910 Version:Current License: Permissive (Apache-2.0)
cubesviewerby jjmontesl
JavaScript 419 Version:v2.0.2
cubesviewerby jjmontesl
JavaScript 419 Version:v2.0.2 License: Others (Non-SPDX)
pandasby pandas-dev
Python 36647 Version:1.5.2
pandasby pandas-dev
Python 36647 Version:1.5.2 License: Permissive (BSD-3-Clause)
Machine Learning
We have created a group for Machine Learning which has the libraries used in my solution. The below libraries help in capturing the embeddings for the text. The embeddings are vectorial representations of text with their semantics.
scikit-learnby scikit-learn
Python 52681 Version:1.2.0
scikit-learnby scikit-learn
Python 52681 Version:1.2.0 License: Permissive (BSD-3-Clause)
numpyby numpy
Python 22526 Version:1.24.1
numpyby numpy
Python 22526 Version:1.24.1 License: Permissive (BSD-3-Clause)
label-studioby heartexlabs
Python 11773 Version:1.7.0
label-studioby heartexlabs
Python 11773 Version:1.7.0 License: Permissive (Apache-2.0)
Data Labeling
Libraries in this section are used for annotating data for creating training data for machine learning.
labelboxby Labelbox
JavaScript 1686 Version:1
labelboxby Labelbox
JavaScript 1686 Version:1 License: Permissive (Apache-2.0)
auto-sklearnby automl
Python 6704 Version:v0.14.7
auto-sklearnby automl
Python 6704 Version:v0.14.7 License: Permissive (BSD-3-Clause)
Kit Solution Source
automl-starterby kandikits
Jupyter Notebook 0 Version:Current
automl-starterby kandikits
Jupyter Notebook 0 Version:Current License: Permissive (MIT)
Deployment Information
This section has the instructions to install our solution. For our app, the deployment instructions are: 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
Open Weaver – Develop Applications Faster with Open Source