CppCoreGuidelines
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CppCoreGuidelines | tensorflow | |
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306 | 222 | |
41,497 | 182,456 | |
0.9% | 0.8% | |
7.6 | 10.0 | |
12 days ago | 4 days ago | |
Python | C++ | |
GNU General Public License v3.0 or later | Apache License 2.0 |
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CppCoreGuidelines
- Learn Modern C++
- C++ Core Guidelines
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Modern C++ Programming Course
You need to talk to Bjarne and Herb...
"C++ Core Guidelines" - https://isocpp.github.io/CppCoreGuidelines/CppCoreGuidelines
- CLion Nova Explodes onto the C and C++ Development Scene
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Toward a TypeScript for C++"
In addition to the other comments -
TypeScript deliberately takes a "good enough" approach to improving JavaScript, instead of designing an ideal but incompatible approach. For example, its handling of [function parameter bivariance](https://www.typescriptlang.org/docs/handbook/type-compatibil...) is unsound but works much better with the existing JavaScript ecosystem. By contrast, a more academic functional programming language would guarantee a sound type system but would be a huge shift from JavaScript.
By analogy, Herb Sutter is arguing that something like the [C++ Core Guidelines](https://isocpp.github.io/CppCoreGuidelines/CppCoreGuidelines), with tooling help in this new Cpp2 syntax, can bring real improvements to safety. Something like Rust's borrow checker would bring much stricter guarantees, backed by academic research and careful design, but would be incompatible and a huge adjustment.
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MechE student here. Is there benefit to learning C in addition to C++, or can one do everything with C++ that can be done with C?
https://www.youtube.com/watch?v=2olsGf6JIkU
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C++ is everywhere, but noone really talks about it. What are people's thoughts?
Take a look at Effective Modern c++ by Scott Meyers and the ISO c++ core guidelines. These resources are great for learning how to write better, more modern C++. I don't think it would be hard to grasp if you're already familiar with the language, just make sure to actually write some code which makes use of this stuff, otherwise it's easy to forget.
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What are some C++ specific antipatterns that might be missed by C#/Java devs?
Look to the C++ Core Guidelines. It's not perfect, it has some flaws, including some sabotaging advice apparently adopted for political reasons. But at least it has some C++ authorities (Bjarne and Herb) as authors.
- How to improve the code quality
tensorflow
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Google lays off its Python team
[3]: https://github.com/tensorflow/tensorflow/graphs/contributors
- TensorFlow-metal on Apple Mac is junk for training
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🔥🚀 Top 10 Open-Source Must-Have Tools for Crafting Your Own Chatbot 🤖💬
To get up to speed with TensorFlow, check their quickstart Support TensorFlow on GitHub ⭐
- One .gitignore to rule them all
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10 Github repositories to achieve Python mastery
Explore here.
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GitHub and Developer Ecosystem Control
Part of the major userbase pull in GitHub revolves around hosting a considerable number of popular projects including Angular, React, Kubernetes, cpython, Ruby, tensorflow, and well even the software that powers this site Forem.
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Non-determinism in GPT-4 is caused by Sparse MoE
Right but that's not an inherent GPU determinism issue. It's a software issue.
https://github.com/tensorflow/tensorflow/issues/3103#issueco... is correct that it's not necessary, it's a choice.
Your line of reasoning appears to be "GPUs are inherently non-deterministic don't be quick to judge someone's code" which as far as I can tell is dead wrong.
Admittedly there are some cases and instructions that may result in non-determinism but they are inherently necessary. The author should thinking carefully before introducing non-determinism. There are many scenarios where it is irrelevant, but ultimately the issue we are discussing here isn't the GPU's fault.
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Can someone explain how keras code gets into the Tensorflow package?
and things like y = layers.ELU()(y) work as expected. I wanted to see a list of the available layers so I went to the Tensorflow GitHub repository and to the keras directory. There's a warning in that directory that says:
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Is it even possible to design a ML model without using Python or MATLAB? Like using C++, C or Java?
Exactly what language do you think TensorFlow is written in? :)
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How to do deep learning with Caffe?
You can use Tensorflow's deep learning API for this.
What are some alternatives?
Crafting Interpreters - Repository for the book "Crafting Interpreters"
PaddlePaddle - PArallel Distributed Deep LEarning: Machine Learning Framework from Industrial Practice (『飞桨』核心框架,深度学习&机器学习高性能单机、分布式训练和跨平台部署)
github-cheat-sheet - A list of cool features of Git and GitHub.
Prophet - Tool for producing high quality forecasts for time series data that has multiple seasonality with linear or non-linear growth.
LearnOpenGL - Code repository of all OpenGL chapters from the book and its accompanying website https://learnopengl.com
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
git-internals-pdf - PDF on Git Internals
LightGBM - A fast, distributed, high performance gradient boosting (GBT, GBDT, GBRT, GBM or MART) framework based on decision tree algorithms, used for ranking, classification and many other machine learning tasks.
Power-Fx - Power Fx low-code programming language
scikit-learn - scikit-learn: machine learning in Python
clojure-style-guide - A community coding style guide for the Clojure programming language
LightFM - A Python implementation of LightFM, a hybrid recommendation algorithm.