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
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-learn: machine learning in Python
Python 54399 Version:1.2.2 License: Permissive (BSD-3-Clause)
A library for efficient similarity search and clustering of dense vectors.
C++ 22027 Version:v1.7.4 License: Permissive (MIT)
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.
Flexible and powerful data analysis / manipulation library for Python, providing labeled data structures similar to R data.frame objects, statistical functions, and much more
Python 38499 Version:v2.0.2 License: Permissive (BSD-3-Clause)
The fundamental package for scientific computing with Python.
Python 23587 Version:v1.24.3 License: Permissive (BSD-3-Clause)
Kit Solution Source
Build your faq virtual agent in 5 minutes
Jupyter Notebook 2 Version:Current License: Permissive (Apache-2.0)
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.