incubator-fury
A blazingly fast multi-language serialization framework powered by JIT and zero-copy. (by apache)
pytorch-forecasting
Time series forecasting with PyTorch (by jdb78)
| incubator-fury | pytorch-forecasting | |
|---|---|---|
| 15 | 9 | |
| 2,654 | 3,635 | |
| 3.4% | - | |
| 9.8 | 8.6 | |
| 3 days ago | 7 days ago | |
| Java | Python | |
| Apache License 2.0 | 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.
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.
incubator-fury
Posts with mentions or reviews of incubator-fury.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2024-05-07.
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Rethinking string encoding: a 37.5% space efficient encoding than UTF-8 in Fury
For implemetation details, https://github.com/apache/incubator-fury/blob/main/java/fury... can be taken as an example
- Apache Fury – fast serialization framework – 0.5.0 released
- Fast Cloud Native Java Serialization:Fury JIT and GraalVM Native Image AOT
- Fury Serialization Framework 0.3.1 Released: Support Python 3.11&3.12
- Fury Serialization 0.3.1 Released: support Python 3.11&12
- Fury Serialization Framework 0.3.0 released
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Fury Scala: Fast binary serialization for any Scala 2/3 objects
See https://github.com/alipay/fury/blob/main/docs/guide/scala_gu... for scala serialization user doc
- Fury – Fast multi-language serialization framework powered by JIT and Zero-copy
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Fury: 170x faster than JDK, fast serialization powered by JIT and Zero-copy
Yes, Game is another scenario, it's very latency sensitive. Fury is very fast for such scenarios. Actually the java implememtation has been featured by some game developers. And there has always been a demand within the community for FURY to support C#: https://github.com/alipay/fury/issues/686 . I don't have experience for c#, so c# hasn't been support. We are still the community can join us for c# support.
- FLaNK Stack Weekly for 14 Aug 2023
pytorch-forecasting
Posts with mentions or reviews of pytorch-forecasting.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2023-08-14.
- FLaNK Stack Weekly for 14 Aug 2023
-
Pytorch Lstm
Source: Conversation with Bing, 4/5/2023 (1) jdb78/pytorch-forecasting: Time series forecasting with PyTorch - GitHub. https://github.com/jdb78/pytorch-forecasting. (2) Time Series Prediction with LSTM Using PyTorch - Colaboratory. https://colab.research.google.com/github/dlmacedo/starter-academic/blob/master/content/courses/deeplearning/notebooks/pytorch/Time_Series_Prediction_with_LSTM_Using_PyTorch.ipynb. (3) time-series-classification · GitHub Topics · GitHub. https://github.com/topics/time-series-classification. (4) PyTorch: Dataloader for time series task - Stack Overflow. https://stackoverflow.com/questions/57893415/pytorch-dataloader-for-time-series-task.
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[D] What is the best approach to create embeddings for time series with additional historical events to use with Transformers model?
Temporal fusion transformer https://github.com/jdb78/pytorch-forecasting
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LSTM/CNN architectures for time series forecasting[Discussion]
Pytorch-forecasting
- Can someone help me with this? It's been days that i struggle with this problem, Forecasting w DeepAR
- Can someone help me with this? it's been days that i struggle with this problem
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[P] Beware of false (FB-)Prophets: Introducing the fastest implementation of auto ARIMA [ever].
To name a few: https://github.com/jdb78/pytorch-forecasting, https://github.com/unit8co/darts, https://github.com/Nixtla/neuralforecast
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When to go for an 'easy' time-series model vs. using a complex deep learning model (when having experience with the latter)
I'm a data trainee at this organisation. I wrote my master thesis about using an event clustering mechanism to enrich an existing dataset to improve short-term demand predictions, using Pytorch Forecasting using the temporal fusion transformer component, and LightGBM (and compare the models with and w/o the event feature, so 4 runs in total).
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A python library for easy manipulation and forecasting of time series.
Darts is a pretty nice one. I've recently been using pytorch-forecasting for larger models like the Temporal Fusion Transformer. https://github.com/jdb78/pytorch-forecasting
What are some alternatives?
When comparing incubator-fury and pytorch-forecasting you can also consider the following projects:
jdbc-connector-for-apache-kafka - Aiven's JDBC Sink and Source Connectors for Apache Kafka®
darts - A python library for user-friendly forecasting and anomaly detection on time series.
grpc-dotnet - gRPC for .NET
Prophet - Tool for producing high quality forecasts for time series data that has multiple seasonality with linear or non-linear growth.
fury-benchmarks - Serialization Benchmarks for fury with other libraries
neuralforecast - Scalable and user friendly neural :brain: forecasting algorithms.
MemoryPack - Zero encoding extreme performance binary serializer for C# and Unity.
Lime-For-Time - Application of the LIME algorithm by Marco Tulio Ribeiro, Sameer Singh, Carlos Guestrin to the domain of time series classification
FlatBuffers - FlatBuffers: Memory Efficient Serialization Library
pytorch-lightning - Build high-performance AI models with PyTorch Lightning (organized PyTorch). Deploy models with Lightning Apps (organized Python to build end-to-end ML systems). [Moved to: https://github.com/Lightning-AI/lightning]
qs - Quick serialization of R objects
tslearn - The machine learning toolkit for time series analysis in Python
incubator-fury vs jdbc-connector-for-apache-kafka
pytorch-forecasting vs darts
incubator-fury vs grpc-dotnet
pytorch-forecasting vs Prophet
incubator-fury vs fury-benchmarks
pytorch-forecasting vs neuralforecast
incubator-fury vs MemoryPack
pytorch-forecasting vs Lime-For-Time
incubator-fury vs FlatBuffers
pytorch-forecasting vs pytorch-lightning
incubator-fury vs qs
pytorch-forecasting vs tslearn