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Estefany Suárez provides a conceptual overview of the rudiments of machine learning, including its bases in traditional statistics and the types of questions it might be applied to.

 

The lesson was presented in the context of the BrainHack School 2020.

Difficulty level: Beginner
Duration: 01:22:18
Speaker: :

Jake Vogel gives a hands-on, Jupyter-notebook-based tutorial to apply machine learning in Python to brain-imaging data.

 

The lesson was presented in the context of the BrainHack School 2020.

Difficulty level: Beginner
Duration: 02:13:53
Speaker: :

Gael Varoquaux presents some advanced machine learning algorithms for neuroimaging, while addressing some real-world considerations related to data size and type.

 

The lesson was presented in the context of the BrainHack School 2020.

Difficulty level: Beginner
Duration: 01:17:14
Speaker: :

Dr. Guangyu Robert Yang describes how Recurrent Neural Networks (RNNs) trained with machine learning techniques on cognitive tasks have become a widely accepted tool for neuroscientists. In comparison to traditional computational models in neuroscience, RNNs can offer substantial advantages at explaining complex behavior and neural activity patterns. Their use allows rapid generation of mechanistic hypotheses for cognitive computations. RNNs further provide a natural way to flexibly combine bottom-up biological knowledge with top-down computational goals into network models. However, early works of this approach are faced with fundamental challenges. In this talk, Dr. Guangyu Robert Yang discusses some of these challenges, and several recent steps that we took to partly address them and to build next-generation RNN models for cognitive neuroscience.​

Difficulty level: Beginner
Duration: 00:51:12
Speaker: :

This lecture introduces you to the basics of the Amazon Web Services public cloud. It covers the fundamentals of cloud computing and go through both motivation and process involved in moving your research computing to the cloud. 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: 3:09:12
Speaker: : Amanda Tan

As a part of NeuroHackademy 2020, Tara Madhyastha (University of Washington), Andrew Crabb (AWS), and Ariel Rokem (University of Washington) give a lecture on Cloud Computing, focusing on Amazon Web Services

 

This video is provided by the University of Washington eScience Institute.

 

Difficulty level: Beginner
Duration: 01:43:59
Speaker: :

Shawn Brown presents an overview of CBRAIN, a web-based platform that allows neuroscientists to perform computationally intensive data analyses by connecting them to high-performance-computing facilities across Canada and around the world.

 

This talk was given in the context of a Ludmer Centre event in 2019.

 

 

Difficulty level: Beginner
Duration: 56:07
Speaker: :

In this presentation by the OHBM OpenScienceSIG, Tom Shaw and Steffen Bollmann cover how containers can be useful for running the same software on different platforms and sharing analysis pipelines with other researchers. They demonstrate how to build docker containers from scratch, using Neurodocker, and cover how to use containers on an HPC with singularity.

 

 

Difficulty level: Beginner
Duration: 01:21:59

Serving as good refresher, Shawn Grooms explains the maths and logic concepts that are important for programmers to understand, including sets, propositional logic, conditional statements, and more.

 

This compilation is courtesy of freeCodeCamp.

Difficulty level: Beginner
Duration: 01:00:07
Speaker: :

Linear algebra is the branch of mathematics concerning linear equations such as linear functions and their representations through matrices and vector spaces. As such, it underlies a huge variety of analyses in the neurosciences.  This lesson provides a useful refresher which will facilitate the use of Matlab, Octave, and various matrix-manipulation and machine-learning software.

 

This lesson was created by RootMath.

Difficulty level: Beginner
Duration: 01:21:30
Speaker: :

NWB: An ecosystem for neurophysiology data standardization

Difficulty level: Beginner
Duration: 29:53
Speaker: : Oliver Ruebel

Learn how to create a standard extracellular electrophysiology dataset in NWB using Python

Difficulty level: Intermediate
Duration: 23:10
Speaker: : Ryan Ly

Learn how to create a standard calcium imaging dataset in NWB using Python

Difficulty level: Intermediate
Duration: 31:04
Speaker: : Ryan Ly

Learn how to create a standard intracellular electrophysiology dataset in NWB

Difficulty level: Intermediate
Duration: 20:23
Speaker: : Pamela Baker

Learn how to use the icephys-metadata extension to enter meta-data detailing your experimental paradigm

Difficulty level: Intermediate
Duration: 27:18
Speaker: : Oliver Ruebel

Learn how to build and share extensions in NWB

Difficulty level: Advanced
Duration: 20:29
Speaker: : Ryan Ly

Learn how to build custom APIs for extension

Difficulty level: Advanced
Duration: 25:40
Speaker: : Andrew Tritt

Learn how to handle writing very large data in PyNWB

Difficulty level: Advanced
Duration: 26:50
Speaker: : Andrew Tritt

Learn how to create a standard extracellular electrophysiology dataset in NWB using MATLAB

Difficulty level: Intermediate
Duration: 45:46
Speaker: : Ben Dichter

Learn how to create a standard calcium imaging dataset in NWB using MATLAB

Difficulty level: Intermediate
Duration: 39:10
Speaker: : Ben Dichter