awesome-repositories.comCategoriiBlog
MCP
awesome-repositories.com

Descoperă cele mai bune repository-uri open source cu căutare AI.

ExploreazăCăutări recomandateAlternative open-sourceSoftware self-hostedBlogHartă site
ProiectServer MCPDespreCum realizăm clasamentulPresă
LegalConfidențialitateTermeni
© 2026 Bringes Technology SRL·VAT RO45896025·hello@awesome-repositories.com
·
K

khanhnamle1994/world-cup-2018

0
View on GitHub↗
0 stele·0 fork-uri·2 vizualizări

World Cup 2018

Features

  • Data Analysis - Statistical analysis and squad lineup prediction for international soccer teams.

Istoric stele

Graficul istoricului de stele pentru khanhnamle1994/world-cup-2018Graficul istoricului de stele pentru khanhnamle1994/world-cup-2018

Căutare AI

Explorează mai multe repository-uri excelente

Descrie ce ai nevoie în limbaj simplu — AI-ul sortează mii de proiecte open source selectate în funcție de relevanță.

Start searching with AI

Alternative open-source pentru World Cup 2018

Proiecte open-source similare, clasificate după numărul de funcționalități comune cu World Cup 2018.
  • aws/aws-sdk-pandasAvatar aws

    aws/aws-sdk-pandas

    4,107Vezi pe GitHub↗

    aws-sdk-pandas is a Python library that integrates pandas dataframes with AWS services, acting as a cloud data ETL tool and data lake connector. It provides a unified interface to move and transform data between in-memory dataframes and cloud storage, databases, and data warehouses. The project distinguishes itself as a distributed compute orchestrator capable of submitting pandas-based workloads to EMR clusters and serverless processing environments. It further specializes in coordinating distributed data processing via Ray cluster initialization to handle datasets that exceed the memory of

    Pythonamazon-athenaamazon-sagemaker-notebookapache-arrow
    Vezi pe GitHub↗4,107
  • bididi-badidi/fyp-data-analysis-with-llmAvatar bididi-badidi

    bididi-badidi/FYP-Data-Analysis-With-LLM

    10Vezi pe GitHub↗

    Human interpretation of data is inherently susceptible to cognitive biases. While Large Language Models (LLMs) act as automated data analysts, they often mirror user biases or training artifacts. This project introduces a "Bias-Contrastive" Agentic Framework that goes beyond simple text analysis.

    Python
    Vezi pe GitHub↗10
  • cdslaborg/paramonteAvatar cdslaborg

    cdslaborg/paramonte

    305Vezi pe GitHub↗

    ParaMonte: Parallel Monte Carlo and Machine Learning Library for Python, MATLAB, Fortran, C++, C.

    Fortran
    Vezi pe GitHub↗305
  • alanmarazzi/pantheraAvatar alanmarazzi

    alanmarazzi/panthera

    191Vezi pe GitHub↗

    Data-frames & arrays on Clojure

    Clojure
    Vezi pe GitHub↗191
Vezi toate cele 30 alternative pentru World Cup 2018→

Întrebări frecvente

Care sunt principalele funcționalități ale khanhnamle1994/world-cup-2018?

Principalele funcționalități ale khanhnamle1994/world-cup-2018 sunt: Data Analysis.

Care sunt câteva alternative open-source pentru khanhnamle1994/world-cup-2018?

Alternativele open-source pentru khanhnamle1994/world-cup-2018 includ: aws/aws-sdk-pandas — aws-sdk-pandas is a Python library that integrates pandas dataframes with AWS services, acting as a cloud data ETL… bididi-badidi/fyp-data-analysis-with-llm — Human interpretation of data is inherently susceptible to cognitive biases. While Large Language Models (LLMs) act as… cdslaborg/paramonte — ParaMonte: Parallel Monte Carlo and Machine Learning Library for Python, MATLAB, Fortran, C++, C. data-centric-ai-community/fg-data-profiling — This project is a data profiling and exploratory data analysis tool designed to generate automated quality reports for… desbordante/desbordante-core — Desbordante is a high-performance data profiler that is capable of discovering many different patterns in data using… alanmarazzi/panthera — Data-frames & arrays on Clojure.