Genann
MessagePack
Genann | MessagePack | |
---|---|---|
7 | 22 | |
1,905 | 1,378 | |
- | 0.3% | |
0.0 | 8.1 | |
8 months ago | 10 days ago | |
C | Java | |
zlib License | Apache License 2.0 |
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Genann
- Simple neural network library in ANSI C
- Genann: Simple neural network library in ANSI C
- Machine learning Library in C?
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Ask HN: What ML platform are you using?
> I am very much a beginner in the space of machine learning
While the (precious and useful) advice around seem to cover mostly the bigger infrastructures, please note that
you can effectively do an important slice of machine learning work (study, personal research) with just a battery-efficiency-level CPU (not GPU), in the order of minutes, on a battery. That comes before going to "Big Data".
And there are lightweight tools: I am current enamoured with Genann («minimal, well-tested open-source library implementing feedfordward artificial neural networks (ANN) in C»), a single C file of 400 lines compiling to a 40kb object, yet well sufficient to solve a number of the problems you may meet.
https://codeplea.com/genann // https://github.com/codeplea/genann
After all, is it a good idea to have tools that automate process optimization while you are learning the deal? Only partially. You should build - in general and even metaphorically - the legitimacy of your Python ops on a good C ground.
And: note that you can also build ANNs in R (and other math or stats environments). If needed or comfortable...
Also note - reminder - that the MIT lessons of Prof. Patrick Winston for the Artificial Intelligence course (classical AI with a few lessons on ANNs) are freely available. That covers the grounds relative to climb into the newer techniques.
- Small tensor library in C99
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C Deep
Genann - Simple ANN in C89, without additional dependencies. Zlib
MessagePack
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What is the fastest way to encode the arbitrary struct into bytes?
so appreciate such a detailed reply, thanks. btw, why did you choose tinylib/msgp from 4 available go-impls?
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Using Arduino as input to Rust project (help needed)
If you find you're running the serial connection at maximum speed and it's still not fast enough, try switching to a more compact binary encoding that has both Serde and Arduino implementations, like MsgPack... though I don't remember enough about its format off the top of my head to tell you the easiest way to put an unambiguous header on each packet/message to make the protocol self-synchronizing.
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Java Serialization with Protocol Buffers
The information can be stored in a database or as files, serialized in a standard format and with a schema agreed with your Data Engineering team. Depending on your information and requirements, it can be as simple as CSV, XML or JSON, or Big Data formats such as Parquet, Avro, ORC, Arrow, or message serialization formats like Protocol Buffers, FlatBuffers, MessagePack, Thrift, or Cap'n Proto.
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Multiplayer Networking Solutions
MessagePack Similar to JSONs, just more compact, although not as much as the ones above. Still, it's usefull to retain some readability in your messages.
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Sketch crashes with "Soft WDT reset" randomly (ArduinoJSON and HTTPClient)
I'll try that msgpack.org website.
- Unknown encryption method ?
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GitHub - realtimetech-solution/opack: Fast object or data serialize and deserialize library
First of all, you're comparing this to GSON and Kryo, how does it compare to Msgpack, fast-serialization, but also Elsa and I'm sure, many others? Are there any limitations and/or trade-offs?
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Optimal dispatcher for json messages ?
Upvote for msgpack, one of the great undervalued message protocols available.
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Rust is just as fast as C/C++
I have two suggestions Capnproto, MessagePack (those are only the two examples that came to mind first, i bet there are even one or two especially developed for rust). Both of these are better than json in nearly every way.
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msgspec - a fast & friendly JSON/MessagePack library
Encode messages as JSON or MessagePack.
What are some alternatives?
tiny-cnn - header only, dependency-free deep learning framework in C++14
FlatBuffers - FlatBuffers: Memory Efficient Serialization Library
Recast/Detour - Industry-standard navigation-mesh toolset for games
Kryo - Java binary serialization and cloning: fast, efficient, automatic
frugally-deep - Header-only library for using Keras (TensorFlow) models in C++.
Cap'n Proto - Cap'n Proto serialization/RPC system - core tools and C++ library
tensorflow - An Open Source Machine Learning Framework for Everyone
Protobuf - Protocol Buffers - Google's data interchange format
ANNetGPGPU - A GPU (CUDA) based Artificial Neural Network library
protostuff - Java serialization library, proto compiler, code generator
BayesOpt - BayesOpt: A toolbox for bayesian optimization, experimental design and stochastic bandits.
ZLib - A massively spiffy yet delicately unobtrusive compression library.