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Lesson title:

The probability of a hypothesis, given data.

Difficulty level: Beginner
Duration: : 7:57
Speaker: : Barton Poulson
Course Name: : Foundations of Data Science
Lesson title:

Why math is useful in data science.

Difficulty level: Beginner
Duration: : 1:35
Speaker: : Barton Poulson
Course Name: : Foundations of Data Science
Lesson title:

Why statistics are useful for data science.

Difficulty level: Beginner
Duration: : 4:01
Speaker: : Barton Poulson
Course Name: : Foundations of Data Science
Lesson title:

Statistics is exploring data.

Difficulty level: Beginner
Duration: : 2:23
Speaker: : Barton Poulson
Course Name: : Foundations of Data Science
Lesson title:

Graphical data exploration

Difficulty level: Beginner
Duration: : 8:01
Speaker: : Barton Poulson
Course Name: : Foundations of Data Science
Lesson title:

Numerical data exploration

Difficulty level: Beginner
Duration: : 5:05
Speaker: : Barton Poulson
Course Name: : Foundations of Data Science
Lesson title:

Simple description of statistical data.

Difficulty level: Beginner
Duration: : 10:16
Speaker: : Barton Poulson
Course Name: : Foundations of Data Science
Lesson title:

Basics of hypothesis testing.

Difficulty level: Beginner
Duration: : 06:04
Speaker: : Barton Poulson
Course Name: : Foundations of Data Science
Lesson title:

In this lecture, the speaker demonstrates Neurokernel's module interfacing feature by using it to integrate independently developed models of olfactory and vision LPUs based upon experimentally obtained connectivity information.

Difficulty level: Intermediate
Duration: : 29:56
Speaker: : Aurel A. Lazar
Course Name: : Open collaboration in computational neuroscience
Lesson title:

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
Course Name: : INCF Short course: Introduction to neuroinformatics
Lesson title:

Presentation of a simulation software for spatial model neurons and their networks designed primarily for GPUs.

Difficulty level: Beginner
Duration: : 21:15
Speaker: : Tadashi Yamazaki
Course Name: : Neuromorphic computing and challenges
Lesson title:

Presentation 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
Course Name: : Neuromorphic computing and challenges
Lesson title:

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 Name: : Neuromorphic computing and challenges
Lesson title:

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
Course Name: : Neuromorphic computing and challenges
Lesson title:

This lecture covers structured data, databases, federating neuroscience-relevant databases, ontologies. 

Difficulty level: Beginner
Duration: : 1:30:45
Speaker: : Maryann Martone
Course Name: : INCF Short course: Introduction to neuroinformatics
Lesson title:

An overview of some of the essential concepts in neuropharmacology (e.g. receptor binding, agonism, antagonism), an introduction to pharmacodynamics and pharmacokinetics, and an overview of the drug discovery process relative to diseases of the Central Nervous System.

Difficulty level: Beginner
Duration: : 45:47
Course Name: : Brain medicine for non-specialists