Solar Panel Efficiency Management Model Kit
by sarthakkiran Updated: Jan 9, 2022
Solution Kit
Team Name: VIT/OW/55 "The future is green energy, sustainability, renewable energy. Once you got a solar panel on a roof, energy is free. Once we convert our entire electricity grid to green and renewable energy, the cost of living goes down." Welcome to our Sustainable Energy Management Hackathon kit. Check out our video Report!! https://drive.google.com/file/d/1me1sje1o5Lrm8SkKQpQy9Sx5j_2Itowi/view?usp=sharing
Exploratory Data Analysis in Python
These libraries are used for statistical, Univariate, descriptive, and exploratory analysis.
matplotlibby matplotlib
matplotlib: plotting with Python
matplotlibby matplotlib
Python
17088
Version:v3.7.1
License: No License
seabornby mwaskom
Statistical data visualization in Python
seabornby mwaskom
Python
10513
Version:v0.12.2
License: Permissive (BSD-3-Clause)
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)
numpyby numpy
The fundamental package for scientific computing with Python.
numpyby numpy
Python
23036
Version:v1.24.2
License: Permissive (BSD-3-Clause)
Machine Learning Libraries for Prescriptive Analysis
These libraries are used for developing the machine learning pipeline model .
scikit-learnby scikit-learn
scikit-learn: machine learning in Python
scikit-learnby scikit-learn
Python
53544
Version:1.2.2
License: Permissive (BSD-3-Clause)
pycaretby pycaret
An open-source, low-code machine learning library in Python
pycaretby pycaret
Jupyter Notebook
7086
Version:3.0.0
License: Permissive (MIT)
auto-sklearnby automl
Automated Machine Learning with scikit-learn
auto-sklearnby automl
Python
6802
Version:v0.15.0
License: Permissive (BSD-3-Clause)
Annotation & Labelling libraries
These are used for data visualization, data Labelling, data annotation.
tortusby SiphuLangeni
A PyPI package for easy text annotation in a Jupyter Notebook.
tortusby SiphuLangeni
Python
11
Version:v1.0.2
License: Strong Copyleft (GPL-3.0)
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)
labelboxby Labelbox
Labelbox is the fastest way to annotate data to build and ship computer vision applications.
labelboxby Labelbox
JavaScript
1708
Version:Current
License: Permissive (Apache-2.0)
Deployment Information
This section has the instructions to install the kit. For theSarthak & Ashutosh kit source, the deployment instructions are: 1. Clone our github repository from the source: https://github.com/Sarthak1807/Sustainable-Energy-Hackathon 2. Download and save all your files. 3. For the Prescriptive and Exploratory data analysis, Navigate to the 'energy hack.ipynb' and open and run each cell. 4. For the Statistical and Descriptive, time Series analysis , Navigate to the 'energy hack.ipynb' and open and run each cell. 5. For the Data Labelling and Annotation, Navigate to the 'tortus_labelling.ipynb' and open and run each cell. 6. Install the required libraries by 'pip install -r requirements.txt' 7. Read out report.