Statistics & Machine Learning
Statistics & Machine Learning
Purpose of the collection
These courses will introduce the basics of powerful machine learning techniques and the elements of traditional statistical approaches provide foundational knowledge for multivariate analyses.
- GLM, regression models, and latent variables
- Refresher for regressions models and GLM
- Addition of different noise distributions and advanced models
- Logistic regression
- Latent variables
- Machine learning
- Conceptual overview
- Hands-on application of simple machine learning to neuroscience data
- Advanced models
- Deep learning
- Caveats in deep learning applications to neuroscience
- Statistical software
- scikit-learn
- nilearn
- JASP
Courses in this collection
1
Difficulties experienced in understanding machine learning techniques often stem from lack of clarity concerning more basic statistical models and…
2
This course begins with the conceptual basics of machine learning and then moves on to some Python-based applications of popular supervised learning…
3
These courses give introductions and overviews of some of the major statistics software packages currently used in neuroscience research.