Mage
Data-Science-Roadmap
Mage | Data-Science-Roadmap | |
---|---|---|
77 | 4 | |
7,050 | 2,853 | |
3.5% | - | |
9.9 | 8.7 | |
2 days ago | 5 months ago | |
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.
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.
Mage
- FLaNK AI-April 22, 2024
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A mage on the Heroâs Journey: a fantasy epic on how a startup rose from the ashes
In the coming years, Mage will create a cooperative experience so that developers can build data pipelines with their team and level up together. After that journey, Mage will go on an epic quest to create the 1st open world community experience in the data universe.
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Data sources episode 2: AWS S3 to Postgres Data Sync using Singer
Link to original blog: https://www.mage.ai/blog/data-sources-ep-2-aws-s3-to-postgres-data-sync-using-singer
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What are some open-source ML pipeline managers that are easy to use?
I would recommend the following: - https://www.mage.ai/ - https://dagster.io/ - https://www.prefect.io/ - https://metaflow.org/ - https://zenml.io/home
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Mage Battlegrounds: Craft insights from real-time customer behavior analysis
You're invited to participate in the very first Mage Battlegrounds: Craft insights from real-time customer behavior analysis, a 24-hour virtual hackathon hosted by Shashank Mishra! This data engineering competition will take place on Saturday, April 15, 2023 beginning at 11am (PST). This will be a global event open to all participants who register.
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Looking for an open-source project
Try this feature: https://github.com/mage-ai/mage-ai/issues/1166
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Daskqueue: Dask-based distributed task queue
Seeing if we can use it in https://github.com/mage-ai/mage-ai
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Data Pipeline on a Shoestring
That being said thereâs a solid family of services just breaking ground that make the local pipeline deployment easier (check out https://www.mage.ai, which does have a clear path to cloud deployment of locally developed pipes, it just isnât well documented yet, and also https://www.neuronsphere.io - which doesnât have a public solution YET (theyâre internally testing an alpha) but they built a cloud deployable solution for their paying customers and working to release one for freemium use)
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Trending ML repos of the week đ
7ď¸âŁ mage-ai/mage-ai
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Delta without using Spark
Yes, check out how Mage does it: https://github.com/mage-ai/mage-ai/tree/master/mage_integrations/mage_integrations/destinations/delta_lake_s3
Data-Science-Roadmap
- Road map data science/ machine learning
- Mudança de carreira- programação
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Career Roadmaps
Data science: https://github.com/Moataz-Elmesmary/Data-Science-Roadmap
- Data-Science-Roadmap: Data Science Roadmap from A to Z
What are some alternatives?
dagster - An orchestration platform for the development, production, and observation of data assets.
data-engineer-roadmap - Roadmap to becoming a data engineer in 2021
vscode-dvc - Machine learning experiment tracking and data versioning with DVC extension for VS Code
stat-cookbook - :orange_book: The probability and statistics cookbook
sqlmesh - Efficient data transformation and modeling framework that is backwards compatible with dbt.
Data-Science-Cheatsheet - A helpful 5-page machine learning cheatsheet to assist with exam reviews, interview prep, and anything in-between.
mito - The mitosheet package, trymito.io, and other public Mito code.
awesome_time_series_in_python - This curated list contains python packages for time series analysis
Airflow - Apache Airflow - A platform to programmatically author, schedule, and monitor workflows
Portfolio-Guide - A guide and summary to my projects and case studies.
Data-science - Collection of useful data science topics along with articles, videos, and code
www.mlcompendium.com - The Machine Learning & Deep Learning Compendium was a list of references in my private & single document, which I curated in order to expand my knowledge, it is now an open knowledge-sharing project compiled using Gitbook.