La Biblia de la IA - The Bible of AI™ Journal

Educational Research on Artificial Intelligence - ISSN 2695-6411

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Spatial autocorrelation 29 de November de 2023
One in a Million – CC-BY-NC by Thomas Hawk Day 29 of 30DayMapChallenge: « Population » (previously). Setup library(tidyverse) library(sf) library(glue) library(sfdep) Data French administrative units (régions, département... Continue reading: Spatial autocorrelation
Michael

Towards Data Science

Courage to Learn ML: Demystifying L1 & L2 Regularization (part 3) 29 de November de 2023
Why L0.5, L3, and L4 Regularizations Are UncommonPhoto by Kelvin Han on UnsplashWelcome back to the third installment of ‘Courage to Learn ML: Demystifying L1 & L2 Regularization’ Previously, we delved into the purpose of regularization and decoded L1 and L2 methods through the lens of Lagrange Multipliers.Continuing our journey, our mentor-learner duo will further explore L1 […]
Amy Ma

arXiv AI

Transfer Learning between Motor Imagery Datasets using Deep Learning -- Validation of Framework and Comparison of Datasets. (arXiv:2311.16109v1 [cs.CV])
We present a simple deep learning-based framework commonly used in computer vision and demonstrate its effectiveness for cross-dataset transfer learning in mental imagery decoding tasks that are common in the field of Brain-Computer Interfaces (BCI). We investigate, on a large selection of 12 motor-imagery datasets, which ones are well suited for transfer, both as donors […]

VB The Machine

Highlights from the AWS re:Invent keynote: Q AI, strong bedrock foundation, and a smarter cloud 28 de November de 2023
The ‘self-operating’ computer emerges 28 de November de 2023

Montreal AI Ethics Institute

Distributed Governance: a Principal-Agent Approach to Data Governance – Part 1 Background & Core Definitions 25 de November de 2023

The Hacker News

Iranian Hackers Exploit PLCs in Attack on Water Authority in U.S. 29 de November de 2023
200+ Malicious Android Apps Targeting Iranian Banks: Experts Warn 29 de November de 2023

MedRxiv

Can We Trust Synthetic Data in Medicine? A Scoping Review of Privacy and Utility Metrics 28 de November de 2023 Kaabachi, B., Despraz, J., Meurers, T., Otte, K., Halilovic, M., Prasser, F., Raisaro, J. L.

The AI Microsoft

A conversation with Kevin Scott: What’s next in AI 6 de December de 2022

Google AI

Improving simulations of clouds and their effects on climate 22 de November de 2023 Google AI

Plos Medicine

Long-term vaccination strategies to mitigate the impact of SARS-CoV-2 transmission: A modelling study 28 de November de 2023 Alexandra B. Hogan

Open Community for Ethics in Autonomous and Intelligent Systems

OCEANIS Community Publishes Strategy 2.0 21 de November de 2022

OpenMined open-source community

OpenMined's R5Q3 Padawan Program Graduates 12 de October de 2023

Science Magazine

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European Digital SME Alliance

Serena Dell’Agli joins DIGITAL SME 27 de November de 2023 Lucas Asmelash

European Data Protection Supervisor

Announcing: CPDP Data Protection Day Conference 29 de November de 2023

IEEE Engineering in Medicine & Biology Society

IEEE EMBS Hosts Data Science and Engineering Conference in Malta to Promote Data Revolution in Healthcare, Medicine and Biology 20 de November de 2023 Nancy Zimmerman

European Data Protection Board

CSC re-elects Deputy Coordinator 29 de November de 2023 EDPB

IEEE Technology and Society

Murty Polavarapu elected SSIT President-Elect 2024 28 de November de 2023 Miriam Cunningham

The European Automobile Manufacturers’ Association (ACEA)

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Papers with Code: Trending

/ieit-yuan/ YUAN 2.0: A Large Language Model with Localized Filtering-based Attention

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Machine Learning(Tutorial)

EvalML: a library for automated machine learning and model understanding

16 de May de 2021 2 de April de 2021

EvalML is an AutoML library that builds, optimizes, and evaluates machine learning pipelines using domain-specific objective functions, it is a library for automated machine learning (AutoML) and model understanding, written in Python

Pages: 1 2 3

Machine Learning From Scratch

30 de May de 2020 30 de May de 2020

An extensive list of fundamental machine learning models and algorithms from scratch in vanilla Python.

Pages: 1 2 3

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AutoML: a introduction tutorial about H2O Driverless AI

3 de March de 2020 3 de March de 2020

“H2O has been the driver for building models at scale. We are talking about billions of claims. You can’t do this with standard off the shelf open source techniques”. (H2o.ai).

Resources on learning deeplearning from the Massachusetts Institute of Technology

2 de March de 2020 2 de March de 2020

A great selection of resources on learning deeplearning by Lex Fridman from the Massachusetts Institute of Technology (MIT).

Pages: 1 2

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