tfgo
tensorflow
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tfgo | tensorflow | |
---|---|---|
6 | 221 | |
2,378 | 182,456 | |
- | 0.8% | |
1.5 | 10.0 | |
about 1 month ago | about 15 hours ago | |
Go | C++ | |
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.
tfgo
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Show HN: Carton – Run any ML model from any programming language
eh, awesome! Seems this one, right? https://github.com/galeone/tfgo. Quite many stars.
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Introducing GoFaceRec: A Go-based Face Recognition Tool Using Deep Learning
I'm excited to share a project I've been working on: [GoFaceRec](https://github.com/modanesh/GoFaceRec). This is a face recognition tool built in Go, leveraging the power of MTCNN for face detection and QMagFace for face recognition. The project was born out of a desire to bring the power of deep learning models to the Go community. After much effort, I concluded that the best approach was to convert models to TensorFlow and then work with tfgo, a Go binding to TensorFlow's C API. In GoFaceRec, the input image is first processed, and then its embeddings are compared against the ones already computed from our dataset. If the distance between embeddings falls below a specific threshold, then the face is considered as unknown. Otherwise, the proper label will be printed. The project is tested using Go 1.17 on Ubuntu 20.04. For gocv, the version of OpenCV installed is 4.7. And for tfgo, I installed [this version](https://github.com/galeone/tfgo) instead of the official one. You can install this package by running the following command in your project: > go get github.com/modanesh/[email protected] You can find more detailed instructions on how to use the tool in the [GitHub repository](https://github.com/modanesh/GoFaceRec). I welcome any feedback, suggestions, or contributions to the project. I'm looking forward to seeing how the community uses GoFaceRec and hope it can be a valuable tool for those working on face recognition tasks. Happy coding! 🚀
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Why can't Go be popular for machine learning?
Paolo Galeone has improved bindings (tfgo) that can be used for training and deployment.
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How to train a model for object detection in Golang?
https://github.com/galeone/tfgo here is a very good tutorial. I would suggest starting there.
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What libraries from other languages do you wish were ported over into go?
Tensorflow is actually written in C++, and the python package is just bindings to tensorflow. There are Tensorflow Go bindings: https://github.com/galeone/tfgo.
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Using Time series to make predictions
have you tried your hands at [galeone/tfgo](https://github.com/galeone/tfgo); I've just hello-world it... so can't vouch on efficiency
tensorflow
- 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.
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When the documentation has TODOs
Since you've specifically mentioned ML, here's Tenserflow's GitHub. I'm sure a quick glance through that will change your mind.
What are some alternatives?
Gorgonia - Gorgonia is a library that helps facilitate machine learning in Go.
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)
GoLearn - Machine Learning for Go
Prophet - Tool for producing high quality forecasts for time series data that has multiple seasonality with linear or non-linear growth.
neat
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
go-deep - Artificial Neural Network
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.
libsvm - libsvm go version
scikit-learn - scikit-learn: machine learning in Python
Varis - Golang Neural Network
LightFM - A Python implementation of LightFM, a hybrid recommendation algorithm.