Course:

This lesson provides a hands-on, Jupyter-notebook-based tutorial to apply machine learning in Python to brain-imaging data.

Difficulty level: Beginner

Duration: 02:13:53

Speaker: : Jake Vogel

Course:

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

Difficulty level: Beginner

Duration: 01:17:14

Speaker: : Gael Varoquaux

Course:

This lesson from freeCodeCamp introduces Scikit-learn, the most widely used machine learning Python library.

Difficulty level: Beginner

Duration: 02:09:22

Speaker: :

Course:

In this lecture, attendees will learn about the opportunities and challenges associated with Recurrent Neural Networks (RNNs), which, when trained with machine learning techniques on cognitive tasks, have become a widely accepted tool for neuroscientists.

Difficulty level: Beginner

Duration: 00:51:12

Speaker: : Guangyu Robert Yang

Course:

This lecture covers modeling the neuron in silicon, modeling vision and audition, and sensory fusion using a deep network.

Difficulty level: Beginner

Duration: 1:32:17

Speaker: : Shih-Chii Liu

This lesson gives an overview of past and present neurocomputing approaches and hybrid analog/digital circuits that directly emulate the properties of neurons and synapses.

Difficulty level: Beginner

Duration: 41:57

Speaker: : Giacomo Indiveri

Presentation of the Brian neural simulator, where models are defined directly by their mathematical equations and code is automatically generated for each specific target.

Difficulty level: Beginner

Duration: 20:39

Speaker: : Giacomo Indiveri

Course:

This lesson gives an introduction to the Mathematics chapter of Datalabcc's Foundations in Data Science series.

Difficulty level: Beginner

Duration: 2:53

Speaker: : Barton Poulson

Course:

This lesson serves a primer on elementary algebra.

Difficulty level: Beginner

Duration: 3:03

Speaker: : Barton Poulson

Course:

This lesson provides a primer on linear algebra, aiming to demonstrate how such operations are fundamental to many data science.

Difficulty level: Beginner

Duration: 5:38

Speaker: : Barton Poulson

Course:

In this lesson, users will learn about linear equation systems, as well as follow along some practical use cases.

Difficulty level: Beginner

Duration: 5:24

Speaker: : Barton Poulson

Course:

This talk gives a primer on calculus, emphasizing its role in data science.

Difficulty level: Beginner

Duration: 4:17

Speaker: : Barton Poulson

Course:

This lesson clarifies how calculus relates to optimization in a data science context.

Difficulty level: Beginner

Duration: 8:43

Speaker: : Barton Poulson

Course:

This lesson covers Big O notation, a mathematical notation that describes the limiting behavior of a function as it tends towards a certain value or infinity, proving useful for data scientists who want to evaluate their algorithms' efficiency.

Difficulty level: Beginner

Duration: 5:19

Speaker: : Barton Poulson

Course:

This lesson serves as a primer on the fundamental concepts underlying probability.

Difficulty level: Beginner

Duration: 7:33

Speaker: : Barton Poulson

Serving as good refresher, this lesson 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: 1:00:07

Speaker: : Shawn Grooms

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: 1:21:30

Speaker: :

This lecture covers a lot of post-war developments in the science of the mind, focusing first on the cognitive revolution, and concluding with living machines.

Difficulty level: Beginner

Duration: 2:24:35

Speaker: : Paul F.M.J. Verschure

This lecture provides an overview of depression (epidemiology and course of the disorder), clinical presentation, somatic co-morbidity, and treatment options.

Difficulty level: Beginner

Duration: 37:51

Speaker: : Barbara Sperner-Unterweger

This lesson is part 1 of 2 of a tutorial on statistical models for neural data.

Difficulty level: Beginner

Duration: 1:45:48

Speaker: : Jonathan Pillow

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