BitPredict
Polymarket
Block&Token.com
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PostgresML
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Hugging Face
BitPredict is a crypto prediction platform where users forecast Bitcoin, Ethereum, and other cryptocurrency prices, compete on public leaderboards, and build a verified track record with time-stamped prediction receipts - all without risking real money.
BitPredict PostgresMLBitPredict's answer
BitPredict turns crypto predictions into verifiable public receipts. Instead of claiming you predicted a market move after it happened, every prediction is timestamped, tracked, and permanently recorded. This creates a transparent leaderboard where traders, analysts, and crypto enthusiasts can prove their forecasting skills based on actual performance rather than screenshots or hindsight claims.
BitPredict's answer
Most crypto platforms focus on trading, betting, or market data. BitPredict focuses on reputation. Users can build a public track record, compete on leaderboards, follow top predictors, and showcase their prediction accuracy without risking capital. It's the simplest way to prove your market insight and earn credibility within the crypto community.
BitPredict's answer
BitPredict is built for crypto traders, market analysts, content creators, influencers, and blockchain enthusiasts who want to test, track, and showcase their market predictions. Whether you're a professional trader or someone passionate about crypto markets, BitPredict helps you establish a transparent record of your forecasting performance.
BitPredict's answer
BitPredict was created to solve a common problem in the crypto industry: anyone can claim they predicted a market move after it happens. We wanted to create a platform where predictions are recorded before the outcome is known, making accuracy measurable and transparent. By combining public prediction receipts, leaderboards, and performance tracking, BitPredict helps separate genuine market insight from hindsight bias.
BitPredict's answer
BitPredict is built using modern web technologies designed for speed, scalability, and real-time data processing. The platform leverages cloud infrastructure, secure APIs, responsive frontend frameworks, and market data integrations to deliver accurate prediction tracking, public leaderboards, and performance analytics.
BitPredict's answer
BitPredict is used by a growing community of crypto traders, analysts, investors, and content creators worldwide. While we respect the privacy of our users and do not publicly disclose customer information, our platform serves individuals and communities actively involved in cryptocurrency markets.
Based on our record, PostgresML seems to be more popular. It has been mentiond 7 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.
The web service supports generating embeddings from OpenAI and Ollama AI models. It also provides a fallback for users without access to AI models running on a remote server through PostgresML. - Source: dev.to / over 1 year ago
That's outside of the database, though. This is more like what I had in mind -- I just found it: https://postgresml.org/. - Source: Hacker News / over 2 years ago
Some excellent tools were created to represent these tasks "naturally" in SQL and even let most of the computation happen inside the database. PostgresML is a great example. It's built above PostgreSQL and provides a set of functions that allow you to train and use machine learning models with SQL. Here's how you can train a classification model for the classic handwritten digit recognition problem:. - Source: dev.to / over 2 years ago
PostgresML | You know Postgres. Now you know machine learning – PostgresML. - Source: dev.to / over 2 years ago
You can swap in almost any open-source model on Huggingface. HuggingFaceH4/zephyr-7b-beta, Gryphe/MythoMax-L2-13b, teknium/OpenHermes-2.5-Mistral-7B and more.If you haven't seen us here before, we're PostgresML, an open-source MLOps platform built on Postgres. We bring ML to the database rather than the other way around. Source: almost 3 years ago
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