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155 results

SI335 SI335
Unit 8 Class 36: QuickSelect

How do you (quickly!) find the median of an array? Find out!

29:18
Unit 8 Class 36: QuickSelect

95 views

4 years ago

Andreas Mueller
Applied ML 2020 - 12 - AutoML (plus some feature selection)

The second part of the feature selection lecture, plus an overview of automl approaches. Sorry for the chat window, I didn't realize ...

1:25:39
Applied ML 2020 - 12 - AutoML (plus some feature selection)

3,839 views

5 years ago

Joey DeVilla
Sorting out sorting...1981 computer graphics style!

Here's a 1981 film — and yes, it was a *film* — that uses what would've been state-of-the-art graphics at the start of the 8-bit era to ...

30:57
Sorting out sorting...1981 computer graphics style!

16,581 views

8 years ago

ConfEngine
Mastering feature selection: basics to develop your own algo by Dr. Saptarsi Goswami #ODSC_India

After the talk, participants will appreciate the need for feature selection, the basic principles of feature selection algorithm and ...

46:39
Mastering feature selection: basics to develop your own algo by Dr. Saptarsi Goswami #ODSC_India

925 views

6 years ago

Churchill CompSci Talks
Randomised Computation

Randomised Computation, by Daria Dicu Abstract: Randomised algorithms are the simplest and fastest known solution to many ...

31:09
Randomised Computation

2,327 views

9 years ago

Andreas Mueller
Applied Machine Learning 2019 - Lecture 12 - Model Interpretration and Feature Selection

Feature importance measures, partial dependence plots. Univariate and multivariate feature selection, recursive feature selection.

1:17:05
Applied Machine Learning 2019 - Lecture 12 - Model Interpretration and Feature Selection

4,667 views

6 years ago

Musicombo
Grailsort - "Smart" Block Select vs. Many Different Inputs

"Smart" block select sort is a much improved variant of Grailsort's original "naive" block select sort. It's been one of the goals for a ...

26:26
Grailsort - "Smart" Block Select vs. Many Different Inputs

3,999 views

5 years ago

Andreas Mueller
Applied ML 2020 - 11 - Model Inspection and Feature Selection

Course materials at https://www.cs.columbia.edu/~amueller/comsw4995s20/schedule/

1:15:15
Applied ML 2020 - 11 - Model Inspection and Feature Selection

5,037 views

5 years ago

Itnig
What algorithm to choose and how to apply it to your product?

Machine learning and algorithms are two concepts and words that are thrown around a lot these days, but very few actually know ...

1:05:56
What algorithm to choose and how to apply it to your product?

4,364 views

8 years ago

All Things Open
Dungeons, Dragons, and Graph Databases - Guy Royse

Presented by: Guy Royse, Redis Labs Presented at All Things Open 2020 - Databases Track Abstract: Are you an adventurer?

51:41
Dungeons, Dragons, and Graph Databases - Guy Royse

1,207 views

5 years ago

CampusX
Feature Importance using Random Forest and Decision Trees | How is Feature Importance calculated

This video breaks down the process using Random Forest and Decision Trees, making it easy to comprehend. Learn how these ...

27:20
Feature Importance using Random Forest and Decision Trees | How is Feature Importance calculated

63,676 views

4 years ago

ICTP Quantitative Life Sciences
Bandit Algorithms - 1

Speaker: T. LATTIMORE Winter School on Quantitative Systems Biology: Learning and Artificial Intelligence (smr 3246) ...

1:34:05
Bandit Algorithms - 1

10,842 views

7 years ago

TrentDoesMath
Hands On Data Science Project: Understand Customers with KMeans Clustering in Python

Try CodeCrafters for free using my referral link: https://app.codecrafters.io/join?via=trentpark8800 In this walkthrough, we dive into ...

1:47:49
Hands On Data Science Project: Understand Customers with KMeans Clustering in Python

86,799 views

1 year ago

Vuk Rosić
This is BORING But Will Make You Top 0.1% - Conditional Distribution, Multivariate Normal Dist - EP4

Full cource on probability for AI Research ...

21:09
This is BORING But Will Make You Top 0.1% - Conditional Distribution, Multivariate Normal Dist - EP4

392 views

2 months ago

Society of Research Software Engineering
Nicola Martin: Improving performance of Python code for processing Earth Observation Data with GPUs

A talk from the GPU performance parallel session at RSECon2022. Details: ...

25:42
Nicola Martin: Improving performance of Python code for processing Earth Observation Data with GPUs

96 views

2 years ago

Sebastian Wild (research)
Hypersuccinct Trees

This is the long version of my presentation of our ESA 2021 paper on space-efficient tree data structures “Hypersuccinct Trees ...

33:30
Hypersuccinct Trees

78 views

4 years ago

OpenGeoHub Foundation Official Channel
Madlene Nussbaum: Mastering ML for spatial prediction II - model selection and interpretation

Participants will learn how machine learning methods can be used to select covariates through covariate importance of e.g. ...

1:14:01
Madlene Nussbaum: Mastering ML for spatial prediction II - model selection and interpretation

320 views

6 years ago

Universität Bern
Einstein Lectures 2019, Shafi Goldwasser, Pseudo Deterministic Algorithms and Proofs

Shafi Goldwasser describes what is known about pseudo-deterministic algorithms in the sequential, sub-linear and parallel ...

1:08:45
Einstein Lectures 2019, Shafi Goldwasser, Pseudo Deterministic Algorithms and Proofs

826 views

6 years ago

ResEcon 703 - UMass Amherst
Week 2: R Tutorial | Video 5: Data in R

... analysis so for example there's a mutate function that adds new variables select that picks variables filter that picks observations ...

24:53
Week 2: R Tutorial | Video 5: Data in R

932 views

5 years ago

Musicombo
Iterative Bitonic Sort

Visit our community Discord here: https://discord.com/invite/2xGkKC2 Check out the program here: ...

23:41
Iterative Bitonic Sort

31,896 views

4 years ago