Welcome to the DeepMind UNIQ internship training course. This repository was made to introduce basic concepts within the powerful scikit-learn framework. It is divided into two modules in the form of colab notebooks:
-
Introducing Scikit Learn from the Python Data Science Handbook
- Data Representation
- Scikit-Learn's Estimator API
- Supervised toy example
- Unsupervised toy example
- Hand-written digits toy example
-
A colab notebook outlining a use case of
scikit-learnin a real-world data science problem encountered as part of the HumBug project.- Data input processing
- Dataset creation
- Data feature extraction and pre-processing
- Model instantiation and prediction
- Model performance metrics
The task lists for each session are found here:
The training sessions are designed to be informal, so feel free to dive deep into any aspect of each task that may interest you. The task lists are designed to guide you through the material. For any help, please consult the module lead and demonstrators who are here to help you explore the content.
If you have any comments or suggestions to improve the material, please contact Ivan Kiskin.