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489 results

R Consortium
useR! 2020: A method for deriving information from running R code (M. van der Loo), regular

This video is part of the virtual useR! 2020 conference. Find supplementary material on our website https://user2020.r-project.org/.

16:31
useR! 2020: A method for deriving information from running R code (M. van der Loo), regular

410 views

5 years ago

Complexity Explorer
3.10 Enumeration and Exploration of a System's Behavior

Unit 3 Module 10 Algorithmic Information Dynamics: A Computational Approach to Causality and Living Systems---From Networks ...

12:59
3.10 Enumeration and Exploration of a System's Behavior

659 views

7 years ago

Genetic Improvement Workshop
Generating Objected-Oriented Source Code Using Genetic Programming

Using machine learning to generate source code is an active and highly important research area. It has been shown that genetic ...

16:06
Generating Objected-Oriented Source Code Using Genetic Programming

147 views

4 years ago

Genetic Improvement Workshop
Q&A: CRNRepair: Automated Program Repair of Chemical Reaction Networks

Chemical reaction networks (CRNs) are abstractions of distributed networks that form the foundations of many natural phenomena ...

9:46
Q&A: CRNRepair: Automated Program Repair of Chemical Reaction Networks

11 views

4 years ago

Raphaël Millière
How Do Transformers Learn Variable Binding in Symbolic Programs?

Video abstract of the paper "How Do Transformers Learn Variable Binding in Symbolic Programs?" by Yiwei Wu, Atticus Geiger, ...

6:13
How Do Transformers Learn Variable Binding in Symbolic Programs?

360 views

7 months ago

Genetic Improvement Workshop
CRNRepair: Automated Program Repair of Chemical Reaction Networks

Chemical reaction networks (CRNs) are abstractions of distributed networks that form the foundations of many natural phenomena ...

15:02
CRNRepair: Automated Program Repair of Chemical Reaction Networks

52 views

4 years ago

R Consortium
useR! 2020: metashiny: build Shiny apps with a Shiny app (B. Wang), lightning

This video is part of the virtual useR! 2020 conference. Find supplementary material on our website https://user2020.r-project.org/.

4:06
useR! 2020: metashiny: build Shiny apps with a Shiny app (B. Wang), lightning

613 views

5 years ago

Genetic Improvement Workshop
Exploring the Accuracy - Energy Trade-off in Machine Learning

Machine learning accounts for considerable global electricity demand and resulting environmental impact, as training a large ...

15:15
Exploring the Accuracy - Energy Trade-off in Machine Learning

64 views

4 years ago

Genetic Improvement Workshop
Q&A: Exploring the Accuracy - Energy Trade-off in Machine Learning

Machine learning accounts for considerable global electricity demand and resulting environmental impact, as training a large ...

9:02
Q&A: Exploring the Accuracy - Energy Trade-off in Machine Learning

23 views

4 years ago

CodeOps HQ
Setting Up the Perfect Developer Environment on Linux for 2025

Want to learn how to build your own dev tools? Check out CodeCrafters: https://bitly.cx/HFm4 Are you a developer looking to ...

11:58
Setting Up the Perfect Developer Environment on Linux for 2025

344,071 views

1 year ago

UBC_CPSC_103 _screencasts
Module 7: How to Design Analaysis Programs example: Part 3

I can see that main is based on a function composition and the template comes from the How to Design Analysis programs ...

4:37
Module 7: How to Design Analaysis Programs example: Part 3

4,385 views

7 years ago

Yann Herklotz
OOPSLA '21: Formal Verification of High-Level Synthesis

So HTL is a representation of a finite state-machine with datapath and it is therefore mainly composed of a datapath which maps ...

15:00
OOPSLA '21: Formal Verification of High-Level Synthesis

111 views

4 years ago

Matt Williams
How to run Python scripts in JupyterLab

Running Python in JupyterLab can be tricky the first time. This video shows how to write and save scripts and run them in the ...

4:40
How to run Python scripts in JupyterLab

40,596 views

5 years ago

UBC_CPSC_103 _screencasts
Module 7: How to Design Analysis Programs: Part 1

Now that we know what information we have to work with let's start working through the how to design analysis programs recipe.

6:26
Module 7: How to Design Analysis Programs: Part 1

6,091 views

7 years ago

Hardware.ai
5 Ways Pi Pico 2 Takes Your Projects to the Next Level

From enhanced machine learning capabilities to more powerful PIOs and increased memory - among the changes in RP2350 / Pi ...

5:15
5 Ways Pi Pico 2 Takes Your Projects to the Next Level

48,215 views

1 year ago

DHIS2
Module 3 - Session 5 - Sharing

Learning objectives for this session The objective of this session is to see sharing of objects within DHIS2 in action.

4:18
Module 3 - Session 5 - Sharing

4,002 views

7 years ago

Genetic Improvement Workshop
Q&A: Applying Automated Program Repair to Dataflow Programming Languages

Dataflow programming languages are used in a variety of settings, and defects in their programs can have serious consequences.

7:02
Q&A: Applying Automated Program Repair to Dataflow Programming Languages

41 views

4 years ago

Shanmuga R
Python for Beginners - Learn Python Now Without IDE - 2

Python beginner tutorial encourages you to learn by doing. Follow along this Python course to get started. This is Part 2 of the ...

9:15
Python for Beginners - Learn Python Now Without IDE - 2

103 views

3 years ago

NCWIT
2.3 The Importance of Data

This video explains the importance of gathering baseline data as you gear up for change in your department. A variety of data ...

7:36
2.3 The Importance of Data

42 views

6 years ago

NPTEL IIT Bombay
Lecture 24 : Data structure based programming : Part 1 : Introduction

Data structure based programming : Part 1 : Introduction.

5:04
Lecture 24 : Data structure based programming : Part 1 : Introduction

5,632 views

6 years ago

NPTEL IIT Bombay
Week 2-Lecture 13 : Demo of Weka

Week 2-Lecture 13 : Demo of Weka.

8:02
Week 2-Lecture 13 : Demo of Weka

3,451 views

5 years ago

Jibesh Patra
Semantic Bug Seeding: A Learning-Based Approach for Creating Realistic Bugs

When working on techniques to address the wide-spread problem of software bugs, one often faces the need for a large number ...

9:59
Semantic Bug Seeding: A Learning-Based Approach for Creating Realistic Bugs

289 views

4 years ago

NPTEL IIT Bombay
Lecture 22 : Part 5 : Implementing a class with automated memory management 1

Representing variable length entities: Part 5 : Implementing a class with automated memory management 1.

16:19
Lecture 22 : Part 5 : Implementing a class with automated memory management 1

4,041 views

6 years ago

Casey Fiesler
The AI Bias Before Christmas

... to use machine learning to automate the naughty/nice list and discover an important lesson about historical data and AI bias.

4:46
The AI Bias Before Christmas

1,408 views

2 years ago

NPTEL IIT Bombay
Lecture 9 : Loops in various applications Part 1 :  Brute force algorithms

Loops in various applications Part 1 : Loops in various applications brute force algorithms.

17:09
Lecture 9 : Loops in various applications Part 1 : Brute force algorithms

9,224 views

6 years ago