VIT Hackathon Sample Submission Kit
by kandikits 
Updated: Jan 8, 2022
Solution Kit
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
2925 Version:CurrentAn easy to use, self-service open BI reporting and BI dashboard platform.
CBoardby TuiQiao
JavaScript 2925 Version:Current License: Permissive (Apache-2.0)
cubesviewerby jjmontesl
419 Version:v2.0.2Explore and visualize analytical datasets
cubesviewerby jjmontesl
JavaScript 419 Version:v2.0.2 License: Others (Non-SPDX)
pandasby pandas-dev
38499 Version:v2.0.2Flexible 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 38499 Version:v2.0.2 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
54399 Version:1.2.2scikit-learn: machine learning in Python
scikit-learnby scikit-learn
Python 54399 Version:1.2.2 License: Permissive (BSD-3-Clause)
numpyby numpy
23587 Version:v1.24.3The fundamental package for scientific computing with Python.
numpyby numpy
Python 23587 Version:v1.24.3 License: Permissive (BSD-3-Clause)
label-studioby heartexlabs
13103 Version:1.7.3Label Studio is a multi-type data labeling and annotation tool with standardized output format
label-studioby heartexlabs
Python 13103 Version:1.7.3 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
1718 Version:CurrentLabelbox is the fastest way to annotate data to build and ship computer vision applications.
labelboxby Labelbox
JavaScript 1718 Version:Current License: Permissive (Apache-2.0)
auto-sklearnby automl
6954 Version:v0.15.0Automated Machine Learning with scikit-learn
auto-sklearnby automl
Python 6954 Version:v0.15.0 License: Permissive (BSD-3-Clause)
Kit Solution Source
automl-starterby kandikits
0 Version:CurrentThis 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
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