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This lecture provides an introductory overview of some of the most important concepts in software engineering.

Difficulty level: Beginner
Duration: 32:59
Speaker: : Jeff Muller

In this lesson, you will learn in more detail about neuromorphic computing, that is, non-standard computational architectures that mimic some aspect of the way the brain works. 

Difficulty level: Intermediate
Duration: 10:08
Speaker: : Dan Goodman

This video provides a very quick introduction to some of the neuromorphic sensing devices, and how they offer unique, low-power applications.

Difficulty level: Intermediate
Duration: 2:37
Speaker: : Dan Goodman

This video gives a brief introduction to Neuro4ML's lessons on neuromorphic computing - the use of specialized hardware which either directly mimics brain function or is inspired by some aspect of the way the brain computes. 

Difficulty level: Intermediate
Duration: 3:56
Speaker: : Dan Goodman
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 presents a simulation software for spatial model neurons and their networks designed primarily for GPUs.

Difficulty level: Intermediate
Duration: 21:15
Speaker: : Tadashi Yamazaki

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

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 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

This lesson serves a primer on elementary algebra.

Difficulty level: Beginner
Duration: 3:03
Speaker: : Barton Poulson

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

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

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

Difficulty level: Beginner
Duration: 4:17
Speaker: : Barton Poulson

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

Difficulty level: Beginner
Duration: 8:43
Speaker: : Barton Poulson

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

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 computational principles that growth cones employ to detect and respond to environmental chemotactic gradients, focusing particularly on growth-cone shape dynamics.

Difficulty level: Intermediate
Duration: 26:12
Speaker: : Geoff Goodhill