Keras
llvm-project
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Keras | llvm-project | |
---|---|---|
77 | 349 | |
60,937 | 25,563 | |
0.6% | 4.0% | |
9.9 | 10.0 | |
about 17 hours ago | about 12 hours ago | |
Python | C++ | |
Apache License 2.0 | GNU General Public License v3.0 or later |
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.
Keras
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My Favorite DevTools to Build AI/ML Applications!
As a beginner, I was looking for something simple and flexible for developing deep learning models and that is when I found Keras. Many AI/ML professionals appreciate Keras for its simplicity and efficiency in prototyping and developing deep learning models, making it a preferred choice, especially for beginners and for projects requiring rapid development.
- Release: Keras 3.3.0
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Getting Started with Gemma Models
After setting the variables for the environment, the next step is to install dependencies. To use Gemma, KerasNLP is the dependency used. KerasNLP is a collection of natural language processing (NLP) models implemented in Keras and runnable on JAX, PyTorch, and TensorFlow.
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Keras 3.0
All breaking changes are listed here: https://github.com/keras-team/keras/issues/18467
You can use this migration guide to identify and fix each of these issues (and further, making your code run on JAX or PyTorch): https://keras.io/guides/migrating_to_keras_3/
- Keras 3: A new multi-back end Keras
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Can someone explain how keras code gets into the Tensorflow package?
I'm guessing the "real" keras code is coming from the keras repository. Is that a correct assumption? How does that version of Keras get there? If I wanted to write my own activation layer next to ELU, where exactly would I do that?
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How popular are libraries in each technology
Other popular machine learning tools include PyTorch, Keras, and Scikit-learn. PyTorch is an open-source machine learning library developed by Facebook that is known for its ease of use and flexibility. Keras is a high-level neural networks API that is written in Python and is known for its simplicity. Scikit-learn is a machine learning library for Python that is used for data analysis and data mining tasks.
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List of AI-Models
Click to Learn more...
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Official Question Thread! Ask /r/photography anything you want to know about photography or cameras! Don't be shy! Newbies welcome!
I'm not aware of anything off-the-shelf, but if you have sufficient programming experience, one way to do this would be to build a large dataset of reference images and pictures and use something like keras to train a convolutional neural network on them.
- free categorical predictive analytic software?
llvm-project
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Ask HN: Which books/resources to understand modern Assembler?
'Computer Architeture: A Quantitative Apporach" and/or more specific design types (mips, arm, etc) can be found under the Morgan Kaufmann Series in Computer Architeture and Design.
"Getting Started with LLVM Core Libraries: Get to Grips With Llvm Essentials and Use the Core Libraries to Build Advanced Tools "
"The Architecture of Open Source Applications (Volume 1) : LLVM" https://aosabook.org/en/v1/llvm.html
"Tourist Guide to LLVM source code" : https://blog.regehr.org/archives/1453
llvm home page : https://llvm.org/
llvm tutorial : https://llvm.org/docs/tutorial/
llvm reference : https://llvm.org/docs/LangRef.html
learn by examples : C source code to 'llvm' bitcode : https://stackoverflow.com/questions/9148890/how-to-make-clan...
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Flang-new: How to force arrays to be allocated on the heap?
See
https://github.com/llvm/llvm-project/issues/88344
https://fortran-lang.discourse.group/t/flang-new-how-to-forc...
- The LLVM Compiler Infrastructure
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Programming from Top to Bottom - Parsing
You can never mistake type_declaration with an identifier, otherwise the program will not work. Aside from that constraint, you are free to name them whatever you like, there is no one standard, and each parser has it own naming conventions, unless you are planning to use something like LLVM. If you are interested, you can see examples of naming in different language parsers in the AST Explorer.
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Look ma, I wrote a new JIT compiler for PostgreSQL
> There is one way to make the LLVM JIT compiler more usable, but I fear it’s going to take years to be implemented: being able to cache and reuse compiled queries.
Actually, it's implemented in LLVM for years :) https://github.com/llvm/llvm-project/commit/a98546ebcd2a692e...
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C++ Safety, in Context
> It's true, this was a CVE in Rust and not a CVE in C++, but only because C++ doesn't regard the issue as a problem at all. The problem definitely exists in C++, but it's not acknowledged as a problem, let alone fixed.
Can you find a link that substantiates your claim? You're throwing out some heavy accusations here that don't seem to match reality at all.
Case in point, this was fixed in both major C++ libraries:
https://github.com/gcc-mirror/gcc/commit/ebf6175464768983a2d...
https://github.com/llvm/llvm-project/commit/4f67a909902d8ab9...
So what C++ community refused to regard this as an issue and refused to fix it? Where is your supporting evidence for your claims?
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Clang accepts MSVC arguments and targets Windows if its binary is named clang-cl
For everyone else looking for the magic in this almost 7k lines monster, look at line 6610 [1].
[1] https://github.com/llvm/llvm-project/blob/8ec28af8eaff5acd0d...
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Rewrite the VP9 codec library in Rust
Through value tracking. It's actually LLVM that does this, GCC probably does it as well, so in theory explicit bounds checks in regular C code would also be removed by the compiler.
How it works exactly I don't know, and apparently it's so complex that it requires over 9000 lines of C++ to express:
https://github.com/llvm/llvm-project/blob/main/llvm/lib/Anal...
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Fortran 2023
https://github.com/llvm/llvm-project/blob/main/flang/docs/F2...
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MiniScript Ports
• Go • Rust • Lua • pure C (sans C++) • 6502 assembly • WebAssembly • compiler backends, like LLVM or Cranelift
What are some alternatives?
MLP Classifier - A handwritten multilayer perceptron classifer using numpy.
zig - General-purpose programming language and toolchain for maintaining robust, optimal, and reusable software.
scikit-learn - scikit-learn: machine learning in Python
Lark - Lark is a parsing toolkit for Python, built with a focus on ergonomics, performance and modularity.
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
gcc
xgboost - Scalable, Portable and Distributed Gradient Boosting (GBDT, GBRT or GBM) Library, for Python, R, Java, Scala, C++ and more. Runs on single machine, Hadoop, Spark, Dask, Flink and DataFlow
SDL - Simple Directmedia Layer
tensorflow - An Open Source Machine Learning Framework for Everyone
cosmopolitan - build-once run-anywhere c library
Prophet - Tool for producing high quality forecasts for time series data that has multiple seasonality with linear or non-linear growth.
windmill - Open-source developer platform to turn scripts into workflows and UIs. Fastest workflow engine (5x vs Airflow). Open-source alternative to Airplane and Retool.