eserie/wax-ml
A Python library for machine-learning and feedback loops on streaming data
This tool helps scientists, traders, or operations engineers analyze and model time-series data, especially for real-time decisions. It takes streaming data, like sensor readings or financial ticks, to produce predictions or control signals. It's designed for practitioners who need to implement online learning, filtering, or feedback loops for dynamic systems.
No commits in the last 6 months. Available on PyPI.
Use this if you work with continuous streams of data and need to apply advanced machine learning or statistical algorithms for online analysis, forecasting, or control, especially if you're comfortable with Python data tools like pandas and xarray.
Not ideal if your primary task involves batch processing static datasets, or if you're not familiar with programming in Python.
Stars
64
Forks
6
Language
Python
License
Apache-2.0
Category
Last pushed
Apr 21, 2023
Commits (30d)
0
Dependencies
9
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/eserie/wax-ml"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Higher-rated alternatives
explosion/thinc
🔮 A refreshing functional take on deep learning, compatible with your favorite libraries
google-deepmind/optax
Optax is a gradient processing and optimization library for JAX.
patrick-kidger/diffrax
Numerical differential equation solvers in JAX. Autodifferentiable and GPU-capable....
google/grain
Library for reading and processing ML training data.
patrick-kidger/equinox
Elegant easy-to-use neural networks + scientific computing in JAX. https://docs.kidger.site/equinox/