Software Alternatives, Accelerators & Startups

DataSource.ai VS Numerai

Compare DataSource.ai VS Numerai and see what are their differences

DataSource.ai logo DataSource.ai

Community-funded data science tournaments

Numerai logo Numerai

Hedge fund that crowdsources market trading from AI programmers over the Internet
  • DataSource.ai Landing page
    Landing page //
    2023-08-26
  • Numerai Landing page
    Landing page //
    2023-06-15

DataSource.ai features and specs

  • Wide Range of Competitions
    DataSource.ai offers a variety of data science tournaments, providing opportunities for users to engage with diverse datasets and problems, thereby enhancing their learning and skill development across different domains.
  • Community Engagement
    The platform fosters a community of data enthusiasts and professionals where members can collaborate, share solutions, and learn from each other, promoting a sense of camaraderie and collective growth.
  • Skill Development
    Participants can improve their data science skills by working on real-world problems with community feedback and access to a repository of past solutions to learn from.
  • Career Opportunities
    By participating in these competitions, users can improve their visibility in the data science community, which might lead to potential job offers and networking opportunities with industry professionals.

Possible disadvantages of DataSource.ai

  • Highly Competitive Environment
    The competitive nature of data science tournaments might be intimidating for beginners, potentially discouraging them from participating or fully engaging with the challenges.
  • Limited Support for Beginners
    While the community is active, the platform might lack structured resources or mentoring programs specifically aimed at helping newcomers start and progress effectively in data science competitions.
  • Time-Consuming
    Participating in data science tournaments can be time-intensive, which might be challenging for individuals who have to balance other professional or personal commitments.
  • Quality Variance in Datasets
    Not all datasets and competitions might have the same level of quality or relevance, which can be a constraint for participants seeking specific learning outcomes or industry-aligned challenges.

Numerai features and specs

  • Innovative Crowdsourcing Model
    Numerai utilizes a crowdsourced approach to hedge fund management, inviting data scientists worldwide to contribute predictive models for stock market forecasts. This approach encourages diverse ideas and has the potential to improve forecast accuracy.
  • Data Anonymization
    Numerai provides data that is anonymized and purified, which allows data scientists to focus on modeling without worrying about privacy concerns and protecting proprietary data.
  • Potential Earnings
    Participants can earn rewards in the form of the cryptocurrency Numeraire (NMR) based on the performance of their models, which provides a financial incentive for contributing high-quality models.
  • Transparent Performance Monitoring
    Numerai provides a transparent performance evaluation system, allowing contributors to track the effectiveness of their models and see how they stack up against others in the community.
  • Community Collaboration
    The platform fosters a sense of community among data scientists, encouraging them to share ideas, collaborate, and learn from one another through forums and various competitions.

Possible disadvantages of Numerai

  • Complexity of Modeling
    Creating predictive models for financial markets is inherently complex and requires a deep understanding of data science and statistical methods, which may not be suitable for novice data scientists.
  • Volatility of Earnings
    Given that rewards are paid in cryptocurrency (NMR), the value of earnings may be subject to high volatility, which can affect the financial stability of potential earnings from model contributions.
  • Limited Data Visibility
    Due to the anonymized nature of the data provided, contributors may miss certain nuances and context that could be useful for building more effective models.
  • Competition Intensity
    Being a globally open platform, Numerai attracts a large number of participants, which means high competition and potentially lower chances of achieving top-tier rewards.
  • Dependence on Platform
    Contributors' success is heavily dependent on the stability and integrity of the Numerai platform, which can be a risk factor if there are changes to platform policies or rewards structures.

DataSource.ai videos

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Numerai videos

Numerai Starter Pack #1: Intro to Numerai

More videos:

  • Review - Richard Craib: WallStreetBets, Numerai, and the Future of Stock Trading | Lex Fridman Podcast #159
  • Review - E729: Founder Richard Craib shares A.I. hedge fund Numerai, blockchain & mission to manage world’s $

Category Popularity

0-100% (relative to DataSource.ai and Numerai)
Development
43 43%
57% 57
Education & Reference
100 100%
0% 0
Data Collaboration
0 0%
100% 100
Online Learning
45 45%
55% 55

User comments

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Social recommendations and mentions

Based on our record, Numerai seems to be more popular. It has been mentiond 19 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.

DataSource.ai mentions (0)

We have not tracked any mentions of DataSource.ai yet. Tracking of DataSource.ai recommendations started around May 2021.

Numerai mentions (19)

  • Cryptographers Solve Decades-Old Privacy Problem
    For example the Numerai hedge fund's data science tournament for crowdsourced stock market prediction is giving out their expensive hedge fund quality data to their users but it's transformed enough that the users don't actually know what the data is, yet the machine learning models are still working on it. To my knowledge it's not homomorphic encryption because that would be still too computational expensive, but... - Source: Hacker News / over 1 year ago
  • Stock Market Charts You Never Saw
    If you are interested in the machine learning part, you can try the Numerai tournament ( http://numer.ai ). They provide obfuscated high quality hedge fund data that participants can train their models on and send back only their predictions and then they combine the user's predictions into their market neutral meta model which they actively trade. So far their fund's returns looks promising in their category... - Source: Hacker News / over 2 years ago
  • [P] Seeking collaboration with VERY experience ML scientist (Lucrative opportunity)
    This does not solve your problem, but you would be interested in https://numer.ai which is a "wisdom of the crowds" ML competition for stock market predictions. Source: over 2 years ago
  • Ask HN: Who is hiring? (January 2022)
    Company: Numerai (https://numer.ai) Position: Web Developer Location: San Francisco (Remote/On-site with WFH days) Numerai is a new kind of hedge fund powered by thousands of competing data scientists from around the world, all working to predict the stock market. - Source: Hacker News / over 3 years ago
  • Finally did it: I made a crypto trading bot that automatically places orders on new listings before they get added on Binance
    Also it seems you would enjoy the numer.ai stock prediction hedge fund tournament if you didn't already know about it. It's interesting not because of their token, and it's not about pump & dumps but because it's about providing actually useful stock predictions using machine learning models and getting rewarded for it. And you don't have to worry about the technical details of the trade execution on exchanges. So... Source: over 3 years ago
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What are some alternatives?

When comparing DataSource.ai and Numerai, you can also consider the following products

Crowd AnalytiX - Crowd AnalytiX is a data science community and a perfect solution for businesses that want to take advantage of AI but don’t have the in-house expertise or resources.

Colaboratory - Free Jupyter notebook environment in the cloud.

Kaggle - Kaggle offers innovative business results and solutions to companies.

Explorium - Explorium is an External Data Platform that offers ML and AI-based datasets so data scientists can take part in data science competitors and marathons to win prizes.

Machine Hack - Machine Hack is the Machine Learning competition and assessment platform that makes it easy for data scientists, engineers, and business professionals to learn, compete, and get hired.

Infosec Skills - Infosec Skills is technical expertise and engineering development knowledge-building platform where engineers and technical experts can come together to share and learn about the latest security development techniques and strategies.