Introduction to deep learning
The estimated time to complete this training module is 3h.
The prerequisites to take this module are:
- the installation module.
- the python data analysis module (recommended for Python familiarity).
Contact Desiree Lussier if you have questions on this module, or if you want to check that you completed successfully all the exercises.
The first portion of this module was presented by Blake Richards during Brainhack School 2020
The video presentation is available here:
- Watch the video presentation by Blake Richards.
- Consider these statements/questions and answer them briefly in a saved doc:
- Give an example of a research question that you could use deep learning to solve.
- How would deep learning provide an advantage for solving the problem?
- Give an example of a research question for which deep learning would not be appropriate.
- What would be a disadvantage of deep learning compared to another method?
- Follow up with Désirée Lussier to validate you completed the exercise correctly.
- 🎉 🎉 🎉 you completed this training module! 🎉 🎉 🎉
You can check out the documentation on Pytorch and additional tutorials here. The Deep Learning Book by Ian Goodfellow and Yoshua Bengio and Aaron Courville is also freely available here