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What is Kaggle?

Kaggle is a large-scale AI, machine learning, and data science platform that serves as a collaborative ecosystem for developers, researchers, organizations, and AI enthusiasts to build, evaluate, and advance artificial intelligence technologies. The platform functions as a global AI proving ground where users can participate in machine learning competitions, benchmark evaluations, hackathons, educational programs, and open research initiatives designed to test and improve modern AI systems. Kaggle provides access to a massive collection of public datasets, pre-trained machine learning models, reproducible notebooks, and cloud-based computing resources that support real-world AI experimentation and development across industries and research domains. Developers and data scientists can use Kaggle’s notebook environments with free GPU and TPU access to train models, analyze datasets, create machine learning workflows, and share reproducible research with the broader AI community. The platform hosts thousands of machine learning competitions co-developed with leading organizations, research labs, and technology companies, allowing participants to solve complex AI problems involving natural language processing, computer vision, predictive analytics, reasoning systems, and generative AI. Kaggle Benchmarks enables researchers and organizations to publish and evaluate frontier AI models using open-source benchmark SDKs and crowdsourced evaluation frameworks that help measure model performance, factual accuracy, reasoning ability, and domain-specific capabilities. Organizations can also host private hackathons, launch enterprise AI challenges, identify top technical talent, and gather community-driven insights through large-scale competitions and collaborative evaluations.

What is Conseris?

Conseris accounts provide the flexibility to generate an unlimited number of datasets for a single, affordable monthly fee. You can easily duplicate your current datasets with just a click or establish unique field sets for each dataset as needed. Data can be entered directly into our web application, or you can utilize our mobile app for offline data collection. With a simple code, you can invite an unlimited number of contributors at no extra charge, granting them access to your data. You have the capability to analyze your data from various perspectives with limitless filtering options, automatic aggregations, and suggested visualizations. This feature enables you to understand the structure of your data without the need to create custom charts. Furthermore, your work continues seamlessly beyond the office environment. Designed for dedicated researchers, Conseris ensures that your valuable ideas can thrive outside conventional spaces. Whether you find yourself far from home or in remote locations, Conseris is there to support your research endeavors.

Media

Media

Integrations Supported

AIxBlock
CodeGemma
DagsHub
Devstral
Gemma 2
Gemma 3
Gemma 4
Giskard
Google Workspace
Jupyter Notebook
Obviously AI
PaliGemma 2
Pipedream
QSourcer
Qwen2.5
Qwen3
Rambox
SourceWhale
TranslateGemma
Unsloth

Integrations Supported

API Availability

Has API

API Availability

Pricing Information

Pricing not provided
Free Version

Pricing Information

$12 per user per month
Free Trial Offered?

Supported Platforms

SaaS

Supported Platforms

SaaS
Android
iPhone
iPad

Customer Service / Support

Not specified

Customer Service / Support

Web-Based Support

Training Options

Documentation Hub

Training Options

Documentation Hub
Online Training

Company Facts

Organization Name

Google

Date Founded

1998

Company Location

United States

Company Website

www.kaggle.com

Company Facts

Organization Name

Kuvio Creative

Date Founded

2015

Company Location

United States

Company Website

www.conseris.io

Categories and Features

Crowdsourcing

Not specified

Machine Learning

Not specified

Training

Not specified

Web Dataset Providers

Not specified

Categories and Features

Data Extraction

Disparate Data Collection

Web Dataset Providers

Not specified

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