A Python visualization toolkit, built with PyTorch, for neural networks in PyTorch. Neural networks are often described as "black box". The lack of understanding on how neural networks make predictions enables unpredictable/biased models, causing real harm to society and a loss of trust in AI-as...
This repo contains following CNN visualization techniques implemented in Pytorch: Gradient visualization with vanilla backpropagation Gradient visualization with guided backpropagation[1] Gradient visualization with saliency maps[4] Gradient-weighted [3] class activation mapping[2] Guided, gradient-weighted cla...
Python| R| SQL| Jupyter Notebooks| TensorFlow| Scikit-learn| PyTorch| Tableau| Apache Spark| Matplotlib| Seaborn| Pandas| Hadoop| Docker| Git| Keras| Apache Kafka| AWS| NLP| Random Forest| Computer Vision| Data Visualization| Data Exploration| Big Data| Common Machine Learning Algorithms| Machin...
Nowadays, things have changed, and it's become much easier for beginners to build state-of-the-art deep neural network models using deep learning frameworks likeTensorFlowandPyTorch. You no longer need a Ph.D. to build powerful AI. Here are the steps to build a simple convolutional neural n...
PyTorch-BigGraph: A Large-scale Graph Embedding System Adam Lerer, Ledell Wu, Jiajun Shen, Timothee Lacroix, Luca Wehrstedt, Abhijit Bose, Alex Peysakhovich SysML 2019 AliGraph: A Comprehensive Graph Neural Network Platform Rong Zhu, Kun Zhao, Hongxia Yang, Wei Lin, Chang Zhou, Baole Ai, ...
For the CORA simulation, we use PyTorch 1.9.0 as the deep learning framework and Torch-geometric 1.7.2 as the graph deep learning tool. The CORA dataset visualized in Fig.4auses the force-directed Kamada–Kawai algorithm, where the data are grouped by classes. The coordinates of nodes have...
A pytorch toolkit for structured neural network pruning and layer dependency maintaining This tool will automatically detect and handle layer dependencies (channel consistency) during pruning. It is able to handle various network architectures such as DenseNet, ResNet, and Inception. Seeexamples/test_mod...
et al. PyTorch: an imperative style, high-performance deep learning library. In Advances in Neural Information Processing Systems 32 (NeurIPS 2019) (eds Wallach, H. et al.) (Curran Associates, 2019); https://proceedings.neurips.cc/paper/2019/hash/bdbca288fee7f92f2bfa9f7012727740-Abstract....
Introduction to Deep Learning with PyTorch 4 hr 36.1KLearn how to build your first neural network, adjust hyperparameters, and tackle classification and regression problems in PyTorch. See DetailsStart Course See More Related cheat-sheet Keras Cheat Sheet: Neural Networks in Python Make your own ne...
Specialized in Machine learning, Deep Learning, Distributed ML, and Visualization. Also, he has experience in domains like Retail, Finance, and Travel and has specialized in understanding and coordinat... (展开全部) 喜欢读"Deep Learning with PyTorch: A practical approach to building neural network...