mirror of
https://github.com/oceanprotocol/docs.git
synced 2024-11-26 19:49:26 +01:00
.. | ||
data-engineers.md | ||
README.md | ||
the-data-value-creation-loop.md |
description | cover | coverY |
---|---|---|
Earn $, track data & compute provenance, and get more data | ../.gitbook/assets/cover/data_science_banner.png | 0 |
📊 Data Science
How does Ocean benefit data scientists?
It offers three main benefits:
- Earn. You can earn $ by doing crypto price predictions via Predictoor, by curating data in Data Farming, by doing data challenges, and by selling data & models.
- More Data. Use Compute-to-Data to access private data to run your AI modeling algorithms against, data which was previously inaccessible. Browse Ocean Market and other Ocean-powered markets to find more data to improve your AI models.
- Provenance. The acts of publishing data, purchasing data, and consuming data are all recorded on the blockchain to make a tamper-proof audit trail. Know where your AI training data came from!
How do data scientists start using Ocean?
Here are the most relevant Ocean tools to work with:
- The ocean.py library is built for the key environment of data scientists: Python. It can simply be imported alongside other Python data science tools like numpy, matplotlib, scikit-learn and tensorflow. You can use it to publish & sell data assets, buy assets, transfer ownership, and more.
- Predictoor's pdr-backend repo offers Python-based tools to run bots for crypto prediction or trading.
- And any of the other Ocean tools documented here as well:)
Are there mental models for earning $ in data?
Yes. This section has two other pages which elaborate:
- The Data Value Creation Loop lays out the life cycle of data, and how to focus towards high-value use cases.
- What data is valuable helps think about pricing data.
Further resources
The blog post "How Ocean Can Benefit Data Scientists" elaborates further on the benefits of more data, provenance, and earning.