Kedro
openpilot
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Kedro | openpilot | |
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29 | 839 | |
9,341 | 47,362 | |
1.3% | 1.3% | |
9.7 | 10.0 | |
5 days ago | 2 days 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.
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.
Kedro
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Nextflow: Data-Driven Computational Pipelines
Interesting, thanks for sharing. I'll definitely take a look, although at this point I am so comfortable with Snakemake, it is a bit hard to imagine what would convince me to move to another tool. But I like the idea of composable pipelines: I am building a tool (too early to share) that would allow to lay Snakemake pipelines on top of each other using semi-automatic data annotations similar to how it is done in kedro (https://github.com/kedro-org/kedro).
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A Polars exploration into Kedro
# pyproject.toml [project] dependencies = [ "kedro @ git+https://github.com/kedro-org/kedro@3ea7231", "kedro-datasets[pandas.CSVDataSet,polars.CSVDataSet] @ git+https://github.com/kedro-org/kedro-plugins@3b42fae#subdirectory=kedro-datasets", ]
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What are some open-source ML pipeline managers that are easy to use?
So there's 2 sides to pipeline management: the actual definition of the pipelines (in code) and how/when/where you run them. Some tools like prefect or airflow do both of them at once, but for the actual pipeline definition I'm a fan of https://kedro.org. You can then use most available orchestrators to run those pipelines on whatever schedule and architecture you want.
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How do data scientists combine Kedro and Databricks?
We have set up a milestone on GitHub so you can check in on our progress and contribute if you want to. To suggest features to us, report bugs, or just see what we're working on right now, visit the Kedro projects on GitHub.
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How do you organize yourself during projects?
you could use a project framework like kedro to force you to be more disciplined about how you structure your projects. I'd also recommend checking out this book: Edna Ridge - Guerrilla Analytics: A Practical Approach to Working with Data
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Futuristic documentation systems in Python, part 1: aiming for more
Recently I started a position as Developer Advocate for Kedro, an opinionated data science framework, and one of the things we're doing is exploring what are the best open source tools we can use to create our documentation.
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Python projects with best practices on Github?
You can also check out Kedro, it’s like the Flask for data science projects and helps apply clean code principles to data science code.
- Data Science/ Analyst Zertifikate für den Job Markt?
- What are examples of well-organized data science project that I can see on Github?
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Dabbling with Dagster vs. Airflow
An often overlooked framework used by NASA among others is Kedro https://github.com/kedro-org/kedro. Kedro is probably the simplest set of abstractions for building pipelines but it doesn't attempt to kill Airflow. It even has an Airflow plugin that allows it to be used as a DSL for building Airflow pipelines or plug into whichever production orchestration system is needed.
openpilot
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Tinygrad: Hacked 4090 driver to enable P2P
Yes, but he spent several years in self-driving cars (https://comma.ai), which while interesting is also a space that a lot of players are in, so it's not the same as seeing him back to doing stuff that's a little more out there, especially as pertains to IP.
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Imitation Learning
We have a product for sale: https://comma.ai
We raised $18.1M and have made $28M in lifetime revenue to date.
Where are you getting your narrative?
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Driverless cars immune from traffic tickets in California under current laws
What about comma? https://comma.ai/ Seems like our old friend geohot built exactly what you want.
Positive HN discussion: https://news.ycombinator.com/item?id=36927971
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No USS?
The issue was that the front camera on the windshield couldn’t see under the hood. You misunderstand how easy it is to solve for depth and distance with AI without requiring stereo cameras. Read https://github.com/commaai/openpilot
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What car should I get for Seattle city and some ski/hike driving? Or not get a car at all?
Nice to have: I want to get a self-driving add-on that supports some cars better than others. Not a must but high up on my nice-to-have list.
- I need some help understanding video uploads.
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I am nearing the end of my Kona 2020 lease, and I have an appointment at a dealer tomorrow had some questions about leasing an ioniq 6, hopefully someone can help me out.
EDIT: I probably should have added that I currently have the base model of the Kona the lowest model available, and I am looking for a similar thing in the ioniq 6, because my understanding is that it's fully compatible with the comma.ai device and therefore I am not planning on getting the better on board driving system, the Kona that I got unfortunately was not compatible with that device.
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Tesla: Security Vulnerabilities
I wonder how bad this is compared to the competition. https://comma.ai allows you to add self-driving features to a large number of non-Tesla cars so, if we’re including physical firmware hacks as a threat vector, I’d bet tons of alternative cars (new enough Honda Odysseys, Toyota Siennas, etc: probably anything with adaptive cruise control and lane following) have the same sort of potential vulnerability.
- 2024 highlander has Toyota Security Key Now
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Cruise co-founder and CEO Kyle Vogt resigns
Not sure, but from the first article from 4 years ago:
>Last month, we had 1,209 cars drive a little over 1,000,000 miles
Let's say they've had zero growth since then, so 48,000,000 conservatively?
Actually, from their website [1]:
>100+ million miles driven and 10k users.
[1]: https://comma.ai
What are some alternatives?
Airflow - Apache Airflow - A platform to programmatically author, schedule, and monitor workflows
sunnypilot - sunnypilot is a fork of comma.ai's openpilot, an open source driver assistance system. sunnypilot offers the user a unique driving experience for over 260 supported car makes and models with modified behaviors of driving assist engagements. sunnypilot complies with comma.ai's safety rules as accurately as possible.
luigi - Luigi is a Python module that helps you build complex pipelines of batch jobs. It handles dependency resolution, workflow management, visualization etc. It also comes with Hadoop support built in.
carla - Open-source simulator for autonomous driving research.
Dask - Parallel computing with task scheduling
opendbc - democratize access to car decoder rings
cookiecutter-pytorch - A Cookiecutter template for PyTorch Deep Learning projects.
dragonpilot - dragonpilot - 基於 openpilot 的開源駕駛輔助系統
ploomber - The fastest ⚡️ way to build data pipelines. Develop iteratively, deploy anywhere. ☁️
label-studio - Label Studio is a multi-type data labeling and annotation tool with standardized output format
BentoML - The most flexible way to serve AI/ML models in production - Build Model Inference Service, LLM APIs, Inference Graph/Pipelines, Compound AI systems, Multi-Modal, RAG as a Service, and more!
netron - Visualizer for neural network, deep learning and machine learning models