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BuildWithAI Submission: Sample

by BuildwithAIHack21 Updated: Oct 28, 2021

Describe your solution here. e.g. Our solution is a Mental Health Monitor and Virtual Companion for students in the digital classroom. It acts as a virtual friend to the student and keeps her company during online classes. It also reminds her of class schedules, submissions, and other aspects of the classroom. It monitors for mental wellbeing vitals like class participation, connecting with friends, and sends motivational messages. In future versions, we can add connect with parents, teachers, and other stakeholders to address the well-being and academic excellence in a holistic manner. We have used the below techniques for our solution. 1. Machine learning to train for the virtual conversations for the virtual companion. 2. Data exploration to explore the academic and digital activity data to use in training for predicting behavior patterns

Machine Learning

You may be using multiple libraries for different functions in your solution. Please create one group for each function and add the libraries to each group. e.g. I have created a group for Machine Learning which has the libraries used in my solution. The below libraries helps in capturing the embeddings for the text. The embeddings are vectoral representation of text with their semantics.

scikit-learnby scikit-learn

Python star image 52721 Version:1.2.0

License: Permissive (BSD-3-Clause)

scikit-learn: machine learning in Python

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scikit-learnby scikit-learn

Python star image 52721 Version:1.2.0 License: Permissive (BSD-3-Clause)

scikit-learn: machine learning in Python
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faissby facebookresearch

C++ star image 19023 Version:1.5.3

License: Permissive (MIT)

A library for efficient similarity search and clustering of dense vectors.

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faissby facebookresearch

C++ star image 19023 Version:1.5.3 License: Permissive (MIT)

A library for efficient similarity search and clustering of dense vectors.
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Data Exploration

You may be using multiple libraries for different functions in your solution. Please create one group for each function and add the libraries to each group. e.g. I 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.

pandasby pandas-dev

Python star image 36714 Version:1.5.2

License: Permissive (BSD-3-Clause)

Flexible and powerful data analysis / manipulation library for Python, providing labeled data structures similar to R data.frame objects, statistical functions, and much more

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pandasby pandas-dev

Python star image 36714 Version:1.5.2 License: Permissive (BSD-3-Clause)

Flexible and powerful data analysis / manipulation library for Python, providing labeled data structures similar to R data.frame objects, statistical functions, and much more
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numpyby numpy

Python star image 22550 Version:1.24.1

License: Permissive (BSD-3-Clause)

The fundamental package for scientific computing with Python.

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numpyby numpy

Python star image 22550 Version:1.24.1 License: Permissive (BSD-3-Clause)

The fundamental package for scientific computing with Python.
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Kit Solution Source

faq-virtual-agentby balaji-munusamy

Jupyter Notebook star image 2 Version:Current

License: Permissive (Apache-2.0)

Build your faq virtual agent in 5 minutes

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faq-virtual-agentby balaji-munusamy

Jupyter Notebook star image 2 Version:Current License: Permissive (Apache-2.0)

Build your faq virtual agent in 5 minutes
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Deployment Information

The Kit Solution source group should have library which has the full source code for implementing this solution added here. As described in the guidelines for the hackathon, your hackathon solution built should be added in GitHub as a public project and add it under this group. You can find your library using the FIND feature. You can find your library easily by searching by the full name i.e author/project-name. The below library has been added as a sample representation of the solution source

Please describe specific instructions to easily deploy your hackathon solution. In case of python projects you can specify all your pre-requisite software in a requirements.txt file which can be used to install all dependencies at one go. e.g. pip install -r requirements.txt This will enable a one click install for your kit and ready to deploy You can also include any quick validation steps to verify if the deployment is working.

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