Several GitHub repositories can be consulted for an introduction to solving data challenges:
- Python Data Science Handbook contains the entire Python Data Science Handbook (Jake VanderPlas), in the form of free Jupyter notebooks.
- Awesome Machine Learning is a curated list of awesome machine learning frameworks, libraries and software (by language).
- Data Science IPython Notebooks is huge collection of data science Python notebooks that covers a variety of topcis such as deep learning, big data and statistical algorithms.
- Awesome Data Science is a shortcut path to start studying Data Science.
Other useful tools to visualise data are:
- Data visualisation guide: guides you through 7 important topics linked to data visualisation and it is ordered in growing complexity.
Data innovation resources:
- Data innovation toolkit provides a four-stage framework for managing data projects: Planning, Collecting and Processing, Sharing and Analyzing, and Using and Evaluating.
- Data innovation repository aims to provide a comprehensive, practical collection of the available resources to help people throughout the development of their data initiative.