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Introduction to the central concepts of machine learning, and how they can be applied in Python using the Scikit-learn Package. This lecture was part of the 2018 Neurohackademy, a 2-week hands-on summer institute in neuroimaging and data science held at the University of Washington eScience Institute.

Difficulty level: Intermediate
Duration: 2:22:28
Speaker: : Jake Vanderplas

The lecture covers a brief introduction to neuromorphic engineering, some of the neuromorphic networks that the speaker has developed, and their potential applications, particularly in machine learning.

Difficulty level: Intermediate
Duration: 19:57

This lecture highlights the importance of correct annotation and assignment of location, and updated atlas resources to avoid errors in navigation and data interpretation.

Difficulty level: Intermediate
Duration: 22:04
Speaker: : Trygve Leergard

We are at the exciting technological stage where it has become feasible to represent the anatomy of an entire human brain at the cellular level. In this presentation, the speaker explains that neuroanatomy in the XXI Century has become an effort towards the virtualization and standardization of brain tissue.

Difficulty level: Intermediate
Duration: 25:27
Speaker: : Jacopo Annese

This lecture covers essential features of digital brain models for neuroinformatics.

Difficulty level: Intermediate
Duration: 22:26
Speaker: : Douglas Bowden

This presentation covers the neuroinformatics tools and techniques used and their relationship to neuroanatomy for the Allen atlases of the mouse, developing mouse, and mouse connectional atlas.

Difficulty level: Intermediate
Duration: 23:41
Speaker: : Mike Hawrylycz