automq
ML-For-Beginners
| automq | ML-For-Beginners | |
|---|---|---|
| 8 | 28 | |
| 1,421 | 67,111 | |
| 50.4% | 2.7% | |
| 9.9 | 7.6 | |
| 3 days ago | 12 days ago | |
| Java | HTML | |
| GNU General Public License v3.0 or later | 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.
automq
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Tiered storage won't fix Kafka
I agree with your viewpoint. The crux of the matter is not whether to use tiered storage or not, but what trade-offs have been made in the specific storage architecture and what benefits have been gained. Here(https://github.com/AutoMQ/automq?tab=readme-ov-file#-automq-...) is a qualitative comparison chart of streaming systems including kafka/confluent/redpanda/warpstream/automq. This comparison chart does not have specific numerical comparisons, but purely based on their trade-offs at the storage level, I think this will be of some use to you.
- Streaming Platform Comparision:Kafka/Confluent/Pulsar/AutoMQ/Redpanda/Warpstream
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Show HN: AutoMQ – A Cost-Effective Kafka distro that can autoscale in seconds
Yes, thank you for the clarification. AutoMQ has replaced the topic-partition storage with cloud-native S3Stream (https://github.com/AutoMQ/automq/tree/main/s3stream) library, thereby harnessing the benefits of cloud EBS and S3.
- FLaNK Stack Weekly for 20 Nov 2023
ML-For-Beginners
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Good coding groups for black women?
- https://github.com/microsoft/ML-For-Beginners
Also check out this list Pitt puts out every year:
- FLaNK Stack Weekly for 20 Nov 2023
- ML for Beginners GitHub
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is it worth learning NLP without master degree?
I don't recommend just jumping in into natural language processing directly without understanding artificial intelligence theory. I personally recommend for you to start with the basic stuff (regression, classification, and clustering, for example), and then jump into more advanced topics. You already know software developer stuff, so that's a big step already, and it should be easier to understand some concepts. Maybe follow Microsoft's machine learning for beginners curriculum? It looks like a good roadmap overall to not instantly burn out on nlp
- AI i Machine Learning
- I want to learn more about AI and Machine Learning
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Pocetak ML karijere
https://github.com/microsoft/ML-For-Beginners jel mislis na ovo?
- How could I have known
- GitHub - microsoft/ML-For-Beginners: 12 weeks, 26 lessons, 52 quizzes, classic Machine Learning for all
- How do I reset my career after already getting my masters?
What are some alternatives?
TinyLlama - The TinyLlama project is an open endeavor to pretrain a 1.1B Llama model on 3 trillion tokens.
FLAML - A fast library for AutoML and tuning. Join our Discord: https://discord.gg/Cppx2vSPVP.
memq - MemQ is an efficient, scalable cloud native PubSub system
lego-mindstorms - My LEGO MINDSTORMS projects (using set 51515 electronics)
depthai-python - DepthAI Python Library
pycaret - An open-source, low-code machine learning library in Python
FLaNK-SaoPauloBrazil - FLaNK-SaoPauloBrazil
Data-Science-For-Beginners - 10 Weeks, 20 Lessons, Data Science for All!
trip - Elegant middleware functions for your HTTP clients.
pyVHR - Python framework for Virtual Heart Rate
flatpak - Linux application sandboxing and distribution framework
S2ML-Art-Generator - Multiple notebooks which allow the use of various machine learning methods to generate or modify multimedia content [Moved to: https://github.com/justin-bennington/S2ML-Generators]