Best Application Use of Data & AI
Design & Implementation: Does it work? Is it implementable? Did the team think about the user interface (UI) and user experience (UX)?
Innovation: How innovative / creative / unique is the idea? Was there a novel approach applied to solve the problem?
Technical Complexity: Is the project technically impressive? Complex?
Social Impact: How impactful is the idea? Can it impact the lives of many people in a significant way?
Commercial Viability: Is there business potential?
https://github.com/academic/awesome-datascience - includes data science algorithms to use, tutorials, free courses, tools, machine learning libraries, visualisation tools, youtube channels
https://github.com/josephmisiti/awesome-machine-learning - includes machine learning libraries
We listed below some publicly available data sets that represent collections of unstructured text data that you can use. You are not restricted to using these datasets: feel free to come to work with your own data!
Guardian API - https://open-platform.theguardian.com/documentation/
Twitter API - https://developer.twitter.com/en/docs
IBM Watson API - conversation, language, sentiment and advanced text analytics - https://developer.ibm.com/components/watson-apis/
Open AI API - https://beta.openai.com/examples
A complete list of public APIs you can use https://github.com/public-apis/public-apis
A complete list of machine learning public AIs you can use https://github.com/public-apis/public-apis#machine-learning
A curated list of machine learning frameworks, libraries and software - https://github.com/josephmisiti/awesome-machine-learning
Postman
PyCharm Visual Code Intellij Ultimate Juypter
- Forecasting
- Time Series analysis
- Natural Language Processing
- image recognition
- facial detection
- personalised ml chat apps
- natural language processing
- sentiment analysis
- GPT3
- Computer Vision
- neural networks
- deep learning
Additional Resources: https://beamers.github.io/resources.html