redframes
MLflow
redframes | MLflow | |
---|---|---|
10 | 56 | |
295 | 17,284 | |
- | 1.3% | |
1.4 | 9.9 | |
about 1 year ago | 3 days ago | |
Python | Python | |
BSD 2-clause "Simplified" License | Apache License 2.0 |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
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.
redframes
- What is something you wish there was a Python module for?
- Redframes: General Purpose Data Manipulation Library
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Modern Polars: an extensive side-by-side comparison of Polars and Pandas
I'm not GP, but I find the pandas API incredibly inconsistent and difficult to remember how to do simple transformations. For example, it sometimes overloads operators because it doesn't use built in language features like lambdas. There are reasons for the inconsistency, but using the alternatives like R's tidyverse or Julia's DataFramess.jl is like night and day for me.
I found RedFrames [1] recently which wraps Pandas dataframes with a more consistent interface, it's probably what I'd use if I had to write data transformations that had to be compatible with Pandas.
[1] https://github.com/maxhumber/redframes
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Ask HN: How you maintain your daily log?
[2022-10-23 14:11:15]: Question []: should we use Red Frames (https://github.com/maxhumber/redframes) in addition to Pandas? Criteria for decision? @me #projectLion
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Python 3.11.0 final is now available
If you like writing chain-able pandas, you should check out: https://github.com/maxhumber/redframes
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Add your own custom methods to third-party types with this pattern
I intend to use this pattern in my redframes library to hijack some pd.DataFrame methods.
- GitHub - maxhumber/redframes: [re]ctangular[d]ata[frames]
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Ask HN: What are you doing this weekend?
I'm dog-fooding my new Python data manipulation library, redframes: https://github.com/maxhumber/redframes
To help me prep for my Fantasy Hockey Draft next week!
- redframes, a new data manipulation library for ML and visualization
- Show HN: Redframes, a Python data manipulation library like dplyr
MLflow
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Observations on MLOps–A Fragmented Mosaic of Mismatched Expectations
How can this be? The current state of practice in AI/ML work requires adaptivity, which is uncommon in classical computational fields. There are myriad tools that capture the work across the many instances of the AI/ML lifecycle. The idea that any one tool could sufficiently capture the dynamic work is unrealistic. Take, for example, an experiment tracking tool like W&B or MLFlow; some form of experiment tracking is necessary in typical model training lifecycles. Such a tool requires some notion of a dataset. However, a tool focusing on experiment tracking is orthogonal to the needs of analyzing model performance at the data sample level, which is critical to understanding the failure modes of models. The way one does this depends on the type of data and the AI/ML task at hand. In other words, MLOps is inherently an intricate mosaic, as the capabilities and best practices of AI/ML work evolve.
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My Favorite DevTools to Build AI/ML Applications!
MLflow is an open-source platform for managing the end-to-end machine learning lifecycle. It includes features for experiment tracking, model versioning, and deployment, enabling developers to track and compare experiments, package models into reproducible runs, and manage model deployment across multiple environments.
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Exploring Open-Source Alternatives to Landing AI for Robust MLOps
Platforms such as MLflow monitor the development stages of machine learning models. In parallel, Data Version Control (DVC) brings version control system-like functions to the realm of data sets and models.
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cascade alternatives - clearml and MLflow
3 projects | 1 Nov 2023
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EL5: Difference between OpenLLM, LangChain, MLFlow
MLFlow - http://mlflow.org
- Explain me how websites like Dall-E, chatgpt, thispersondoesntexit process the user data so quickly
- [D] What licensed software do you use for machine learning experimentation tracking?
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Exploring MLOps Tools and Frameworks: Enhancing Machine Learning Operations
MLflow:
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Options for configuration of python libraries - Stack Overflow
In search for a tool that needs comparable configuration I looked into mlflow and found this. https://github.com/mlflow/mlflow/blob/master/mlflow/environment_variables.py There they define a class _EnvironmentVariable and create many objects out of it, for any variable they need. The get method of this class is in principle a decorated os.getenv. Maybe that is something I can take as orientation.
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[D] Is there a tool to keep track of my ML experiments?
I have been using DVC and MLflow since then DVC had only data tracking and MLflow only model tracking. I can say both are awesome now and maybe the only factor I would like to mention is that IMO, MLflow is a bit harder to learn while DVC is just a git practically.
What are some alternatives?
xgboost - Scalable, Portable and Distributed Gradient Boosting (GBDT, GBRT or GBM) Library, for Python, R, Java, Scala, C++ and more. Runs on single machine, Hadoop, Spark, Dask, Flink and DataFlow
clearml - ClearML - Auto-Magical CI/CD to streamline your AI workload. Experiment Management, Data Management, Pipeline, Orchestration, Scheduling & Serving in one MLOps/LLMOps solution
Prophet - Tool for producing high quality forecasts for time series data that has multiple seasonality with linear or non-linear growth.
Sacred - Sacred is a tool to help you configure, organize, log and reproduce experiments developed at IDSIA.
Keras - Deep Learning for humans
zenml - ZenML 🙏: Build portable, production-ready MLOps pipelines. https://zenml.io.
tensorflow - An Open Source Machine Learning Framework for Everyone
guildai - Experiment tracking, ML developer tools
pydeep - Deep learning in Python
dvc - 🦉 ML Experiments and Data Management with Git
skflow - Simplified interface for TensorFlow (mimicking Scikit Learn) for Deep Learning