Nosferican/LuxAI.jl Nosferican/LuxAI.jl

  • Stars
    star
    1
  • Language
    Julia
  • Created about 3 years ago
  • Updated about 3 years ago
Twitter logo Share LinkedIn logo Share Facebook logo Share
Nosferican/LuxAI.jl
github

Nosferican

Reviews

There are no reviews yet. Be the first to send feedback to the community and the maintainers!

Repository Details

An agent for the Kaggle Lux AI Challenge

More Repositories

1

Econometrics.jl

Econometrics in Julia
TeX
67
star
2

WebDriver.jl

A WebDriver / JSON Wire Protocol Binding Compatible with Selenium for the Julia Language.
Julia
39
star
3

UEM.jl

Unobserved Effects Models (Panel Data Econometrics) -> For Beta Test
Julia
7
star
4

NCEI.jl

Interface for the National Centers for Environmental Information (NCEI) API
Julia
7
star
5

Julia-Ecosystem-Analysis

An analysis of the Julia ecosystem as it relates to OSS packages.
Julia
4
star
6

DependenciesParser.jl

Dependency parser for Julia
Julia
4
star
7

SpringerQuarantineBooks.jl

A tool for downloading the Springer Quarantine Books.
Julia
3
star
8

EconJobMarket.jl

Interface for the EconJobMarket Data API using the Julia programming language
Julia
2
star
9

CandidatosEleccionesGeneralesPR2020

Candidaturas para la elección general de PR 2020
HTML
2
star
10

EconUtils.jl

For Dev
Julia
1
star
11

WorldBankDataDive2019ConflictSpendingAsia

DataDive 2019 Conflict and Spending in Asia
Julia
1
star
12

LaTeX_Style_cgu

A neat LaTeX class and template for producing manuscripts, dissertations, and others.
TeX
1
star
13

Learning-the-GitHub-API

Tutorial on how to learn to consume the GitHub API
1
star
14

AEEIncidentes

Julia
1
star
15

UVA-SDS-Sample-Lecture

Materials relevant to the "On Campus" interview for the Teaching Track position
Julia
1
star
16

DonativosPol-ticosPR2020

Información de la Oficina del Contralor Electoral de PR
Julia
1
star
17

ActionSelenium

JavaScript
1
star
18

On-Cluster-Robust-Models-Old

Empirical work commonly deals with heterogeneous in treatment populations with potential clustered sampling design. Current approaches to overcome issues that arise in these cases include weighted least squares, fixed effects models, and cluster robust variance covariance estimators. However, the current solutions often offer sub-optimal performance or practitioners misuse them. This study examines possible disadvantages to using non-cluster robust models and alternative solutions. Some of the contributions include a framework to understand and develop cluster robust models with new advise for practitioners and practical considerations. (JEL C01)
TeX
1
star
19

JBSC

HTML
1
star
20

PRLegVotos

Información sobre las votaciones de medidas legislativas de Puerto Rico.
HTML
1
star