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VIT Hackathon Sample Submission Kit
by kandikits
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.
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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.
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Data Labeling
Libraries in this section are used for annotating data for creating training data for machine learning.
Kit Solution Source
This is our source code updated in GitHub for our VIT hackathon entry. The below repo is an example. Please replace with your source code from GitHub.
Kit Deployment Instructions
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