mlops-python-package VS recs-at-resonable-scale

Compare mlops-python-package vs recs-at-resonable-scale and see what are their differences.

mlops-python-package

Kickstart your MLOps initiative with a flexible, robust, and productive Python package. (by fmind)
AI ML Mlops Package Python
Source Code
fmind.github.io
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recs-at-resonable-scale

Recommendations at "Reasonable Scale": joining dataOps with recSys through dbt, Merlin and Metaflow (by jacopotagliabue)
dbt Deep Learning metaflow recommender-system recsys Serverless reasonable-scale reclist
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InfluxDB - Power Real-Time Data Analytics at Scale
Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality.
www.influxdata.com
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mlops-python-package recs-at-resonable-scale
1 2
353 218
- -
7.4 2.3
about 2 months ago about 1 year ago
Jupyter Notebook Python
Creative Commons Attribution 4.0 MIT License
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
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.

mlops-python-package

Posts with mentions or reviews of mlops-python-package. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2023-06-25.
  • When writing ML software - how do you use TDD?
    2 projects | /r/mlops | 25 Jun 2023
    I always use TDD when I work on serious AI/ML projects. Even if this practice is time-consuming in the short term, it's time efficient in the long run. I prefer to catch bugs as early as possible in my workflow. I recently worked on a MLOps Python package that provides examples to implement best practices like TDD, code coverage and more: https://github.com/fmind/mlops-python-package

recs-at-resonable-scale

Posts with mentions or reviews of recs-at-resonable-scale. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2023-06-25.

What are some alternatives?

When comparing mlops-python-package and recs-at-resonable-scale you can also consider the following projects:

superduperdb - 🔮 SuperDuperDB: Bring AI to your database! Build, deploy and manage any AI application directly with your existing data infrastructure, without moving your data. Including streaming inference, scalable model training and vector search.

Transformers4Rec - Transformers4Rec is a flexible and efficient library for sequential and session-based recommendation and works with PyTorch.

aim - Aim 💫 — An easy-to-use & supercharged open-source experiment tracker.

Activeloop Hub - Data Lake for Deep Learning. Build, manage, query, version, & visualize datasets. Stream data real-time to PyTorch/TensorFlow. https://activeloop.ai [Moved to: https://github.com/activeloopai/deeplake]

metaflow - :rocket: Build and manage real-life ML, AI, and data science projects with ease!

deeplake - Database for AI. Store Vectors, Images, Texts, Videos, etc. Use with LLMs/LangChain. Store, query, version, & visualize any AI data. Stream data in real-time to PyTorch/TensorFlow. https://activeloop.ai

mlops-python-package vs superduperdb recs-at-resonable-scale vs Transformers4Rec mlops-python-package vs aim mlops-python-package vs Activeloop Hub mlops-python-package vs metaflow mlops-python-package vs deeplake