| cuml | nifi | |
|---|---|---|
| 10 | 35 | |
| 3,926 | 4,429 | |
| 1.1% | 2.2% | |
| 9.3 | 9.9 | |
| about 8 hours ago | 2 days ago | |
| C++ | Java | |
| Apache License 2.0 | 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.
cuml
- FLaNK Stack Weekly for 13 November 2023
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Is it possible to run Sklearn models on a GPU?
sklearn can't, bit take a look at cuML (https://github.com/rapidsai/cuml ). It uses the same API as sklearn but executes on GPU.
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[P] Looking for state of the art clustering algorithms
As a companion to the other comments, I'd like to mention that the RAPIDS library cuML provides GPU-accelerated versions of quite a few of the algorithms mentioned in this thread (HDBSCAN, UMAP, SVM, PCA, {Exact, Approximate} Nearest Neighbors, DBSCAN, KMeans, etc.).
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Is there a multi regression model that works on GPU?
CuML
- [D] What's your favorite unpopular/forgotten Machine Learning method?
- Machine Learning with PyTorch and Scikit-Learn – The *New* Python ML Book
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What are the advantages and disadvantages of using GPU for machine learning/ deep learning/ scientific computation over the conventional CPU software acceleration?
Did they implement the clustering algorithm themselves? cuML is a GPU-accelerated scikit-learn-like package that covers many of the common ML algorithms.
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Intel Extension for Scikit-Learn
https://github.com/rapidsai/cuml
> cuML is a suite of libraries that implement machine learning algorithms and mathematical primitives functions that share compatible APIs with other RAPIDS projects. cuML enables data scientists, researchers, and software engineers to run traditional tabular ML tasks on GPUs without going into the details of CUDA programming. In most cases, cuML's Python API matches the API from scikit-learn. For large datasets, these GPU-based implementations can complete 10-50x faster than their CPU equivalents. For details on performance, see the cuML Benchmarks Notebook.
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GPU Based Kernel-PCA
Cython code
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Python Machine Learning Guy getting started with CUDA. What should I be brushing up on?
Take a look at RAPIDS CUML https://github.com/rapidsai/cuml. It's useful for most common ML algorithms. Feel free to create Github issues for feature requests & bugs.
nifi
- FLaNK Stack Weekly 19 Feb 2024
- Ask HN: What are some unpopular technologies you wish people knew more about?
- FLaNK Stack Weekly for 13 November 2023
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Ask HN: What low code platforms are worth using?
Apache NIFI (https://nifi.apache.org/).
It uses the concept of Flow-based programming. Also its so underacknolged but this tool is very flexible. I have used as an Event Bus all the 3rd-Party Integrations.
- Apache Nifi: easy to use, powerful, reliable system to process, distribute data
- Tool decision - What architecture would you choose and why?
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Help with choosing techstack for a new DE team
Presently setting up Apache Nifi + Apache MiNiFi for the ETL portion of my work. NiFi was easy enough to figure out; but the docs for MiNiFi have been a pain due to differences between the Java and C++ versions. I then entirely configured it with the Java version so that it was easier to search for answers for the MiNiFi yaml syntax.
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MS SQL Change Data Capture
Found it
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Is there something like airflow but written in Scala/Java?
Apache Camel Apache Nifi Spring Cloud
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Json splitting and Rerouting (new to nifi)
NIFI, like most Apache projects does most of its discussion on its mailing lists, but also has a slack.
What are some alternatives?
scikit-learn - scikit-learn: machine learning in Python
Logstash - Logstash - transport and process your logs, events, or other data
scikit-learn-intelex - Intel(R) Extension for Scikit-learn is a seamless way to speed up your Scikit-learn application
superset - Apache Superset is a Data Visualization and Data Exploration Platform
scikit-cuda - Python interface to GPU-powered libraries
meltano
hummingbird - Hummingbird compiles trained ML models into tensor computation for faster inference.
meltano - Meltano: the declarative code-first data integration engine that powers your wildest data and ML-powered product ideas. Say goodbye to writing, maintaining, and scaling your own API integrations.
cudf - cuDF - GPU DataFrame Library
Pandas - Flexible and powerful data analysis / manipulation library for Python, providing labeled data structures similar to R data.frame objects, statistical functions, and much more
evojax
Metabase - The simplest, fastest way to get business intelligence and analytics to everyone in your company :yum: