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4 changes: 2 additions & 2 deletions content/material.md
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* Implement a typical model validation pipeline with Scikit-learn
* Learn about various model performance scores and their use-cases

**Materials**: [GitHub Link](https://github.com/neurodatascience/course-materials-2021/tree/master/lectures/29-July/11-intro-to-machine-learning-part-1)
**Materials**: [GitHub Link](https://github.com/neurodatascience/main-2021-ml-parts-1-2)

## Brain encoding and decoding in fMRI
**Instructors**: Shima Rastegarnia and Pravish Sainath
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* Learn about hyperparameters and model selection.
* Learn about pitfalls when validating machine learning models and how to easily avoid them using scikit-learn.

**Materials**: [GitHub Link](https://github.com/neurodatascience/main-2021-ml-part-2)
**Materials**: [GitHub Link](https://github.com/neurodatascience/main-2021-ml-parts-1-2)

## Intro to [Nilearn](https://nilearn.github.io)

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