Forwarded from Tensorflow(@CVision) (Amir Mohammad Ghoreyshi)
نمایش بصری گراف معماری شبکه های عصبی یادگیری عمیق و یادگیری ماشین
Visualizer for neural network, deep learning and machine learning models
Netron is a viewer for neural network, deep learning and machine learning models.
Netron supports ONNX (.onnx, .pb, .pbtxt), Keras (.h5, .keras), Core ML (.mlmodel), Caffe (.caffemodel, .prototxt), Caffe2 (predict_net.pb, predict_net.pbtxt), MXNet (.model, -symbol.json), TorchScript (.pt, .pth), NCNN (.param) and TensorFlow Lite (.tflite).
Netron has experimental support for PyTorch (.pt, .pth), Torch (.t7), CNTK (.model, .cntk), Deeplearning4j (.zip), PaddlePaddle (.zip, model), Darknet (.cfg), scikit-learn (.pkl), TensorFlow.js (model.json, .pb) and TensorFlow (.pb, .meta, .pbtxt).
https://github.com/lutzroeder/netron
Visualizer for neural network, deep learning and machine learning models
Netron is a viewer for neural network, deep learning and machine learning models.
Netron supports ONNX (.onnx, .pb, .pbtxt), Keras (.h5, .keras), Core ML (.mlmodel), Caffe (.caffemodel, .prototxt), Caffe2 (predict_net.pb, predict_net.pbtxt), MXNet (.model, -symbol.json), TorchScript (.pt, .pth), NCNN (.param) and TensorFlow Lite (.tflite).
Netron has experimental support for PyTorch (.pt, .pth), Torch (.t7), CNTK (.model, .cntk), Deeplearning4j (.zip), PaddlePaddle (.zip, model), Darknet (.cfg), scikit-learn (.pkl), TensorFlow.js (model.json, .pb) and TensorFlow (.pb, .meta, .pbtxt).
https://github.com/lutzroeder/netron
GitHub
GitHub - lutzroeder/netron: Visualizer for neural network, deep learning and machine learning models
Visualizer for neural network, deep learning and machine learning models - lutzroeder/netron
A comprehensive list of Neural Architecture Search (NAS) related papers
https://www.automl.org/automl/literature-on-neural-architecture-search/
#machine_learning
https://www.automl.org/automl/literature-on-neural-architecture-search/
#machine_learning
Forwarded from Deep learning channel (Mohsen Fayyaz)
Jeremy Jordan
Organizing machine learning projects: project management guidelines.
The goal of this document is to provide a common framework for approaching machine learning projects that can be referenced by practitioners. If you build ML models, this post is for you.
Machine Learning for Physics and the Physics of Learning Tutorials
https://t.co/4nfcnWkQtM?amp=1
#machine_learning #physics
https://t.co/4nfcnWkQtM?amp=1
#machine_learning #physics
IPAM
Machine Learning for Physics and the Physics of Learning Tutorials (Schedule) - IPAM
New Educational Methods for Learning Mathematics
https://www.youtube.com/watch?v=X_CK1e0Lmxw
#mathematics
https://www.youtube.com/watch?v=X_CK1e0Lmxw
#mathematics
YouTube
Common Core Math Explained
Dr. Raj Shah, owner and founder of Math Plus Academy (mathplusacademy.com) explains why math is taught differently than it was in the past and helps address parents' misconceptions about the "new math". Original video: https://vimeo.com/110807219
François Chollet is the creator of Keras, which is an open source deep learning library that is designed to enable fast, user-friendly experimentation with deep neural networks. It serves as an interface to several deep learning libraries, most popular of which is TensorFlow, and it was integrated into TensorFlow main codebase a while back. Aside from creating an exceptionally useful and popular library, François is also a world-class AI researcher and software engineer at Google, and is definitely an outspoken, if not controversial, personality in the AI world, especially in the realm of ideas around the future of artificial intelligence. This conversation is part of the Artificial Intelligence podcast.
https://www.youtube.com/watch?v=Bo8MY4JpiXE&t=173s
#machine_learning #artificial_intelligence #podcast
https://www.youtube.com/watch?v=Bo8MY4JpiXE&t=173s
#machine_learning #artificial_intelligence #podcast
YouTube
François Chollet: Keras, Deep Learning, and the Progress of AI | Artificial Intelligence Podcast
François Chollet is the creator of Keras, which is an open source deep learning library that is designed to enable fast, user-friendly experimentation with d...
A great and comprehensive review of meta-learning algorithms
https://lilianweng.github.io/lil-log/2018/11/30/meta-learning.html
#meta_learning #deep_learning #machine_learning
https://lilianweng.github.io/lil-log/2018/11/30/meta-learning.html
#meta_learning #deep_learning #machine_learning
Lil'Log
Meta Learning
The purpose of this handout is to help you use statistics to make your argument as effectively as possible, especially in your research paper.
https://writingcenter.unc.edu/tips-and-tools/statistics/
https://writingcenter.unc.edu/tips-and-tools/statistics/
The Writing Center • University of North Carolina at Chapel Hill
Statistics – The Writing Center • University of North Carolina at Chapel Hill
There are lies, damned lies, and statistics. —Mark Twain What this handout is about The purpose of this handout is to help you use statistics to make your argument as effectively as possible. Introduction Numbers are power. Apparently freed of … Read more
Genetic Neural Architecture Search.pdf
1.5 MB
Today I published the pre-print version of my first paper which is about designing a new evolutionary algorithm for neural architecture search in Arxiv.
https://arxiv.org/abs/1909.09432
https://arxiv.org/abs/1909.09432
A set of tutorials and courses on Geometric Deep Learning:
https://people.lu.usi.ch/bronstem/teaching_tutorial.html
#deep_learning #geometric_deep_learning #machine_learning
https://people.lu.usi.ch/bronstem/teaching_tutorial.html
#deep_learning #geometric_deep_learning #machine_learning
A curated list of resources dedicated to Natural Language Processing (NLP)
https://github.com/keon/awesome-nlp
#nlp #deep_learning
https://github.com/keon/awesome-nlp
#nlp #deep_learning
GitHub
GitHub - keon/awesome-nlp: :book: A curated list of resources dedicated to Natural Language Processing (NLP)
:book: A curated list of resources dedicated to Natural Language Processing (NLP) - keon/awesome-nlp