Dream Faster (@dream-faster)
  • Stars
    star
    131
  • Global Org. Rank 50,618 (Top 17 %)
  • Followers 7
  • Registered over 3 years ago
  • Most used languages
    Python
    81.8 %
    TypeScript
    18.2 %
  • Location 🇩🇪 Germany
  • Country Total Rank 9,903
  • Country Ranking
    Python
    1,464
    TypeScript
    4,282

Top repositories

1

fold

🪁 A fast Adaptive Machine Learning library for Time-Series, that lets you build, deploy and update composite models easily. An order of magnitude speed-up, combined with flexibility and rigour. This is an internal project - documentation is not updated anymore and substantially differ from the current API.
Python
84
star
2

krisi

⏳ Evaluation of Time-Series Predictions with powerful pdf and web Reporting. Tailored for evaluation of metrics over time!
Python
20
star
3

fold-wrappers

🧱 Wrappers for 3rd party models to be used with fold (https://github.com/dream-faster/fold)
Python
6
star
4

fold-models

⚙️ Speedy implementations of TS Models, built specifically for Fold (https://github.com/dream-faster/fold)
Python
4
star
5

drift-archive

📈 And end-to-end pipeline to train predictive Machine Learning models on financial (non-stationary, regime changing) time series. Includes feature selection and meta labelling.
Python
4
star
6

modular-pipelines

🐾 A lightweight & extensible library to create complex multi-model and multi-modal pipelines, including ``Ensembles`` and ``Meta-Models``
Python
3
star
7

dream-faster-landing

🏔 This is the landing page for Dream Faster Studio
TypeScript
2
star
8

benchmarks

📐 Time series Benchmarks ran on public Datasets with Fold and Krisi across multiple domains.
TypeScript
2
star
9

laplace-gnn-recommendation

⛓️ laplace is an end-to-end ML framework to train and predict on neurally-enhanced graphs for recommendation. The pipeline is designed for self-supervised edge prediction on heterogenous graphs.
Python
2
star
10

finml-utils

Utility functions of all of our Financial Machine Learning projects
Python
1
star
11

research-neural-symbolic-regression

Python
1
star