Project Name | Stars | Downloads | Repos Using This | Packages Using This | Most Recent Commit | Total Releases | Latest Release | Open Issues | License | Language |
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Tensorflow Examples | 43,109 | 4 months ago | 218 | other | Jupyter Notebook | |||||
TensorFlow Tutorial and Examples for Beginners (support TF v1 & v2) | ||||||||||
Data Science Ipython Notebooks | 25,668 | 7 months ago | 34 | other | Python | |||||
Data science Python notebooks: Deep learning (TensorFlow, Theano, Caffe, Keras), scikit-learn, Kaggle, big data (Spark, Hadoop MapReduce, HDFS), matplotlib, pandas, NumPy, SciPy, Python essentials, AWS, and various command lines. | ||||||||||
Deeplearning Models | 16,142 | 4 months ago | 4 | mit | Jupyter Notebook | |||||
A collection of various deep learning architectures, models, and tips | ||||||||||
Keras Js | 4,879 | 31 | 8 | 2 years ago | 7 | February 09, 2018 | 83 | mit | JavaScript | |
Run Keras models in the browser, with GPU support using WebGL | ||||||||||
Capsnet Tensorflow | 3,678 | 5 years ago | 28 | apache-2.0 | Python | |||||
A Tensorflow implementation of CapsNet(Capsules Net) in paper Dynamic Routing Between Capsules | ||||||||||
Tensorflow Generative Model Collections | 3,570 | 6 years ago | 22 | apache-2.0 | Python | |||||
Collection of generative models in Tensorflow | ||||||||||
Zhihu | 3,228 | 3 years ago | 31 | Jupyter Notebook | ||||||
This repo contains the source code in my personal column (https://zhuanlan.zhihu.com/zhaoyeyu), implemented using Python 3.6. Including Natural Language Processing and Computer Vision projects, such as text generation, machine translation, deep convolution GAN and other actual combat code. | ||||||||||
Deep Learning Keras Tensorflow | 2,863 | 3 years ago | 12 | mit | Jupyter Notebook | |||||
Introduction to Deep Neural Networks with Keras and Tensorflow | ||||||||||
Lingvo | 2,776 | 4 months ago | 133 | apache-2.0 | Python | |||||
Lingvo | ||||||||||
Determined | 2,715 | 1 | 4 months ago | 221 | April 24, 2021 | 142 | apache-2.0 | Go | ||
Determined is an open-source machine learning platform that simplifies distributed training, hyperparameter tuning, experiment tracking, and resource management. Works with PyTorch and TensorFlow. |