polyaxon
intelligent-trading-bot
polyaxon | intelligent-trading-bot | |
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9 | 25 | |
3,483 | 745 | |
0.4% | - | |
8.7 | 8.5 | |
9 days ago | about 1 month ago | |
Python | Python | |
Apache License 2.0 | MIT License |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
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For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
polyaxon
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Any MLOps platform you use?
If you're not concerned about self-hosting, WandB is one of the more fully featured training monitoring tools (I've used it in the past without any issues but the lack of data and training privacy and lack of self-hosting possibilities makes it a hard no for anything that isn't scholastic). Polyaxon is an alternative but rewriting all your variable logging to conform to their requirements makes it very difficult to switch to it in the middle of a project so you have to commit to it from the get-go.
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[D] Kubernetes for ML - how are y'all doing it?
We use Polyaxon and it’s pretty good
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[D] What MLOps platform do you use, and how helpful are they?
Disclosure - I'm the author of Polyaxon.
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Does anyone have experience with polyaxon?
I just came across https://github.com/polyaxon/polyaxon because mlflow gives me a hard time and costs my company money by the day because it is not working as expected.
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[D] Productionalizing machine learning pipelines for small teams
For running experiments, http://polyaxon.com/ is a really good free open-source package that has lots of nice integrations so you can quickly run experiments in k8s but it might be overkill in some cases.
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Top 5 tools to get started with MLOps !
Polyaxon : https://polyaxon.com
- Open source alternative to AWS Sagemaker, Google AI Platform, and Azure ML
intelligent-trading-bot
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TimeGPT-1
I agree that the conventional (numeric) forecasting can hardly benefit from the newest approaches like transformers and LLMs. I made such a conclusion while working on the intelligent trading bot [0] by experimenting with many ML algorithms. Yet, there exist some cases where transformers might provide significant advantages. They could be useful where the (numeric) forecasting is augmented with discrete event analysis and where sequences of events are important. Another use case is where certain patterns are important like those detected in technical analysis. Yet, for these cases much more data is needed.
[0] https://github.com/asavinov/intelligent-trading-bot Intelligent Trading Bot: Automatically generating signals and trading based on machine learning and feature engineering
- intelligent-trading-bot: NEW Other Models - star count:567.0
- intelligent-trading-bot: NEW Other Models - star count:494.0
What are some alternatives?
MLflow - Open source platform for the machine learning lifecycle
binance-trade-bot - Automated cryptocurrency trading bot
kubeflow - Machine Learning Toolkit for Kubernetes
jesse - An advanced crypto trading bot written in Python
flyte - Scalable and flexible workflow orchestration platform that seamlessly unifies data, ML and analytics stacks.
3commas-cyber-bots - 3Commas bot helpers, AltRank, GalaxyScore, Watchlists, Auto-Compound, TrailingStopLoss, TakeProfitIncrement
dvc - 🦉 ML Experiments and Data Management with Git
node-binance-trader - 💰 Cryptocurrency Trading Strategy & Portfolio Management Development Framework for Binance. 🤖
onepanel - The open source, end-to-end computer vision platform. Label, build, train, tune, deploy and automate in a unified platform that runs on any cloud and on-premises.
ANN-decompiler - "AI" demystified: a decompiler
mmlspark - Simple and Distributed Machine Learning [Moved to: https://github.com/microsoft/SynapseML]
shrimpy-python - Shrimpy’s Developer Trading API is a unified way to integrating trading functionality across every major exchange. Collect historical market data, access real-time websockets, execute advanced trading strategies, and manage an unlimited number of users.