Machine Learning School

TLA details

Name
Colab Notebooks
Description
A set of colab notebooks, regarding e.g. these topics: – Applications, e.g. an example of doing OCR, machine translation, etc.; – Fine-tuning a language model (BERT, GPT), e.g. to Shakespeare’s texts; – Fine-tuning a language model to a classification task, e.g. to IMDB; – LSTMs and time series; – Forecasting: ARMA, LSTM, XGBoost, ...; – Optionally also time series decomposition, etc.; – ...
Learning type
Practice
Description Learning through practice enables the learner to adapt their actions to the task goal, and use the feedback to improve their next action. Feedback may come from self-reflection, from peers, from the teacher, or from the activity itself.
Example usage Practising exercises, labs and virtual labs, field trips, simulations, using models, doing practice-based projects,…
Workload
180
Activity delivery
Online
On-site
Hybrid
Synchronous
Asynchronous
Teacher-present
Teacher not present
Collaboration
Work in groups
Feedback

Assessment
Assessment type
Summative
Assessment provider
Teacher
Automated
Peer
Self
Other
Assessment points
0