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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.

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