This lesson gives an in-depth look into various types of neuronal networks, as well properties, parameters, and phenomena which characterize them.

Difficulty level: Beginner

Duration: 1:39:32

Speaker: : Julijana Gjorgjieva

In this lesson, you will learn about spiking neuron networks and linear response models.

Difficulty level: Beginner

Duration: 1:24:22

Speaker: : Tatjana Tchumatchenko

This lesson discusses Bayesian neuron models and parameter estimation.

Difficulty level: Beginner

Duration: 1:12:38

Speaker: : Jakob Macke

This lesson gives an overview of Bayesian memory and learning, as well as how to go from observations to latent variables.

Difficulty level: Beginner

Duration: 1:33:34

Speaker: : Máté Lengyel

In this lesson, you will learn about how constraints can help us understand how the brain works.

Difficulty level: Beginner

Duration: 1:34:42

Speaker: : Simon Laughlin

This lesson discusses how to approach neural systems from an evolutionary perspective.

Difficulty level: Beginner

Duration: 1:29:38

Speaker: : Gilles Laurent

Course:

This talk introduces Bayes' theorem, which describes the probability of an event, based on prior knowledge of conditions that might be related to the event.

Difficulty level: Beginner

Duration: 7:57

Speaker: : Barton Poulson

Course:

This lesson recaps why math, in a number of ways, is extremely useful in data science.

Difficulty level: Beginner

Duration: 1:35

Speaker: : Barton Poulson

Course:

This lesson provides an introduction to the lessons in this course that deal with statistics and why they are useful for data science.

Difficulty level: Beginner

Duration: 4:01

Speaker: : Barton Poulson

Course:

In this lesson, users will learn about the importance of exploratory analysis, as well as how statistics enables one to become familiar with and understand one's data.

Difficulty level: Beginner

Duration: 2:23

Speaker: : Barton Poulson

Course:

This lesson goes over graphical data exploration, including motivations for its use as well as practical examples of visualizing data distributions.

Difficulty level: Beginner

Duration: 8:01

Speaker: : Barton Poulson

Course:

In this lesson, users learn about exploratory statistics, and are introduced to various methods for numerical data exploration.

Difficulty level: Beginner

Duration: 5:05

Speaker: : Barton Poulson

Course:

This lesson overview some simple descriptions of statistical data.

Difficulty level: Beginner

Duration: 10:16

Speaker: : Barton Poulson

Course:

This lesson covers the basics of hypothesis testing.

Difficulty level: Beginner

Duration: 6:04

Speaker: : Barton Poulson

Course:

This lesson provides instruction on how to infer results from incomplete data.

Difficulty level: Beginner

Duration: 4:28

Speaker: : Barton Poulson

Course:

This lesson provides instruction on finding parameter values, computing confidence levels, and other various statistical methods employed in data investigation.

Difficulty level: Beginner

Duration: 08:04

Speaker: : Barton Poulson

Course:

In this lesson, statistical methods and tools are described for estimating parameters in your dataset.

Difficulty level: Beginner

Duration: 5:29

Speaker: : Barton Poulson

Course:

This lesson covers how to measure the correspondece between data and model.

Difficulty level: Beginner

Duration: 3:30

Speaker: : Barton Poulson

Course:

In this lesson, you will learn the concepts behind choosing useful variables, as well as various analyses and tools to do so.

Difficulty level: Beginner

Duration: 6:15

Speaker: : Barton Poulson

Course:

This lesson goes over some of the common problems in statistical modeling.

Difficulty level: Beginner

Duration: 5:58

Speaker: : Barton Poulson

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