BuildWithAI Challenge 1
by BuildwithAIHack21 Updated: Oct 29, 2021
Solution Kit
The Pandemic has impacted education - classes have moved online, students have been isolated on screens and coping with this change. Despite the challenges, the digital school has the potential to transform education. How can we empower students and teachers in this new digital school paradigm. In this challenge, we are inviting AI-powered solutions for the digital school of tomorrow.
DATASET: Feel free to use any dataset of your choice.
There is no restriction and you can use any data set. Please see the section - DATASETS below for sample datasets to help as a reference. Here are sample areas you could choose to tackle in this challenge. Feel free to come up with your own ideas as well. 1. Higher Education and Career Recommendation 2. Mental Health Monitor and Virtual Companion 3. Adaptive Learning Curriculum 4. Class availability scheduling for social distancing 5. Compliance of COVID guidelines - masking, distancing, temperature Please see below for guidelines and reusable libraries to jumpstart your solution. This kit provides reference to open-source libraries which can be reused as core building blocks for creating a predictive solution. You may use any other open-source libraries also as relevant to your solution. Reusability is a key design principle and will be scored positively in your submission. These reference reusable libraries are spread over functions in Data Analysis and Mining, Data Visualization, Machine Learning, and other key areas to build AI solution. Below are the guidelines for creating your submission kit for this challenge. 1. See Product Tour > Creating a kit from the kandi header. This will guide you on creating your kit. 2. Your submission kit should contain the kit heading/ name, description of the solution, and other relevant information. 3. Create groups with logical names and add the libraries to the respective sections. 4. You solution can be built with any libraries other than the libraries provided here for reference. 5. The project source library for the solution built in the hackathon should be hosted in GitHub and listed in your kit under 'Kit Solution Source' section. 6. Any deployment instructions should be added under 'Kit Deployment Instructions' section of the kit. 7. Add any additional information, links under the kit description or group descriptions.DATASETS
https://data.ed.gov/ https://data.world/datasets/education https://data.gov.in/sector/higher-education https://github.com/mdsaifk/Student-Dropout-Prediction/tree/main/Data https://github.com/hilmarh/student-dropout-prediction/tree/master/datasets https://github.com/iampratheesh/Student-Dropout-Prediction/blob/master/student%20info.csv https://www.kaggle.com/spscientist/students-performance-in-exams https://www.kaggle.com/aljarah/xAPI-Edu-Data https://www.kaggle.com/janiobachmann/math-students?select=student-mat.csv https://www.kaggle.com/kwadwoofosu/predict-test-scores-of-students https://www.kaggle.com/namanmanchanda/entrepreneurial-competency-in-university-students https://www.kaggle.com/uciml/student-alcohol-consumption?select=student-por.csv https://www.kaggle.com/passnyc/data-science-for-good https://www.kaggle.com/landlord/education-and-covid19
Development Environment
VSCode and Jupyter Notebook are used for development and debugging. Jupyter Notebook is a web based interactive environment often used for experiments, whereas VSCode is used to get a typical experience of IDE for developers.
notebookby jupyter
Jupyter Interactive Notebook
notebookby jupyter
Jupyter Notebook
9914
Version:v7.0.0a18
License: Permissive (BSD-3-Clause)
Data Analysis and Mining
Data Mining and Analysis plays vital role in Predictive Analytics. It lets you inspect, cleanse, explore, manipulate, transform your data to identify hidden patterns and relationships in data. You can make use of these popular libraries to model the solution.
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
37439
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)
Data Visualization
Data Visualization helps you depict insight found in data. Avail the libraries added here to represent identified patterns and relationships from data graphically for better understanding and presentation.
matplotlibby matplotlib
matplotlib: plotting with Python
matplotlibby matplotlib
Python
17111
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)
grafanaby grafana
The open and composable observability and data visualization platform. Visualize metrics, logs, and traces from multiple sources like Prometheus, Loki, Elasticsearch, InfluxDB, Postgres and many more.
grafanaby grafana
TypeScript
54661
Version:v8.5.22
License: Strong Copyleft (AGPL-3.0)
Text Mining
Libraries in this group are used for analysis and processing of unstructured natural language. The data, as in its original form aren't used as it has to go through processing pipeline to become suitable for applying machine learning techniques and algorithms.
spaCyby explosion
💫 Industrial-strength Natural Language Processing (NLP) in Python
spaCyby explosion
Python
25655
Version:v3.5.1
License: Permissive (MIT)
GloVeby stanfordnlp
GloVe model for distributed word representation
GloVeby stanfordnlp
C
6255
Version:1.2
License: Permissive (Apache-2.0)
CoreNLPby stanfordnlp
Stanford CoreNLP: A Java suite of core NLP tools.
CoreNLPby stanfordnlp
Java
8907
Version:v4.5.4
License: Strong Copyleft (GPL-3.0)
TextBlobby sloria
Simple, Pythonic, text processing--Sentiment analysis, part-of-speech tagging, noun phrase extraction, translation, and more.
TextBlobby sloria
Python
8472
Version:0.7.0
License: Permissive (MIT)
sentence-transformersby UKPLab
Multilingual Sentence & Image Embeddings with BERT
sentence-transformersby UKPLab
Python
9823
Version:v2.2.2
License: Permissive (Apache-2.0)
transformersby huggingface
🤗 Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX.
transformersby huggingface
Python
88853
Version:v4.27.4
License: Permissive (Apache-2.0)
Image Analysis
Image Analysis plays vital role in Visual Analytics. It lets us inspect, cleanse, explore, augment and transform images to prepare data for training and prediction.
scikit-imageby scikit-image
Image processing in Python
scikit-imageby scikit-image
Python
5321
Version:v0.20.0
License: Others (Non-SPDX)
SimpleCVby sightmachine
The Open Source Framework for Machine Vision
SimpleCVby sightmachine
Python
2590
Version:Current
License: Permissive (BSD-3-Clause)
Machine learning algorithms and techniques
To build a model for Predictive Analytics, you can apply traditional machine learning algorithms and techniques using the most popular scikit-learn. Or you can build your own neural network to implement deep learning techniques by using the library of your choice from this section.
scikit-learnby scikit-learn
scikit-learn: machine learning in Python
scikit-learnby scikit-learn
Python
53572
Version:1.2.2
License: Permissive (BSD-3-Clause)
tensorflowby tensorflow
An Open Source Machine Learning Framework for Everyone
tensorflowby tensorflow
C++
172599
Version:v2.12.0
License: Permissive (Apache-2.0)
pytorchby pytorch
Tensors and Dynamic neural networks in Python with strong GPU acceleration
pytorchby pytorch
C++
64612
Version:v2.0.0
License: Others (Non-SPDX)
hubby tensorflow
A library for transfer learning by reusing parts of TensorFlow models.
hubby tensorflow
Python
3284
Version:v0.13.0
License: Permissive (Apache-2.0)
CNTKby microsoft
Microsoft Cognitive Toolkit (CNTK), an open source deep-learning toolkit
CNTKby microsoft
C++
17339
Version:v2.7
License: Others (Non-SPDX)
Theanoby Theano
Theano was a Python library that allows you to define, optimize, and evaluate mathematical expressions involving multi-dimensional arrays efficiently. It is being continued as aesara: www.github.com/pymc-devs/aesara
Theanoby Theano
Python
9691
Version:Current
License: Others (Non-SPDX)
Request servicing via REST API
Web frameworks help build serving solution as REST APIs. The resources involved for servicing request can be handled by containerising and hosting on hyperscalers.
fastapiby tiangolo
FastAPI framework, high performance, easy to learn, fast to code, ready for production
fastapiby tiangolo
Python
56062
Version:0.95.0
License: Permissive (MIT)
flaskby pallets
The Python micro framework for building web applications.
flaskby pallets
Python
62385
Version:2.2.3
License: Permissive (BSD-3-Clause)