5,017 skills found · Page 1 of 168
lutzroeder / NetronVisualizer for neural network, deep learning and machine learning models
karpathy / Char RnnMulti-layer Recurrent Neural Networks (LSTM, GRU, RNN) for character-level language models in Torch
ludwig-ai / LudwigLow-code framework for building custom LLMs, neural networks, and other AI models
GetStream / Vision AgentsOpen Vision Agents by Stream. Build Vision Agents quickly with any model or video provider. Uses Stream's edge network for ultra-low latency.
yahoo / Open NsfwNot Suitable for Work (NSFW) classification using deep neural network Caffe models.
gboeing / OsmnxDownload, model, analyze, and visualize street networks and other geospatial features from OpenStreetMap.
tensorspace-team / TensorspaceNeural network 3D visualization framework, build interactive and intuitive model in browsers, support pre-trained deep learning models from TensorFlow, Keras, TensorFlow.js
locuslab / TCNSequence modeling benchmarks and temporal convolutional networks
amazon-archives / Amazon DsstneDeep Scalable Sparse Tensor Network Engine (DSSTNE) is an Amazon developed library for building Deep Learning (DL) machine learning (ML) models
amanchadha / Coursera Deep Learning SpecializationNotes, programming assignments and quizzes from all courses within the Coursera Deep Learning specialization offered by deeplearning.ai: (i) Neural Networks and Deep Learning; (ii) Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization; (iii) Structuring Machine Learning Projects; (iv) Convolutional Neural Networks; (v) Sequence Models
eragonruan / Text Detection Ctpntext detection mainly based on ctpn model in tensorflow, id card detect, connectionist text proposal network
lucidrains / Musiclm PytorchImplementation of MusicLM, Google's new SOTA model for music generation using attention networks, in Pytorch
diegoantognini / PyGATPytorch implementation of the Graph Attention Network model by Veličković et. al (2017, https://arxiv.org/abs/1710.10903)
IntelLabs / Nlp ArchitectA model library for exploring state-of-the-art deep learning topologies and techniques for optimizing Natural Language Processing neural networks
cbfinn / MamlCode for "Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks"
sherjilozair / Char Rnn TensorflowMulti-layer Recurrent Neural Networks (LSTM, RNN) for character-level language models in Python using Tensorflow
quic / AimetAIMET is a library that provides advanced quantization and compression techniques for trained neural network models.
666DZY666 / Micronetmicronet, a model compression and deploy lib. compression: 1、quantization: quantization-aware-training(QAT), High-Bit(>2b)(DoReFa/Quantization and Training of Neural Networks for Efficient Integer-Arithmetic-Only Inference)、Low-Bit(≤2b)/Ternary and Binary(TWN/BNN/XNOR-Net); post-training-quantization(PTQ), 8-bit(tensorrt); 2、 pruning: normal、regular and group convolutional channel pruning; 3、 group convolution structure; 4、batch-normalization fuse for quantization. deploy: tensorrt, fp32/fp16/int8(ptq-calibration)、op-adapt(upsample)、dynamic_shape
neuralmagic / SparsemlLibraries for applying sparsification recipes to neural networks with a few lines of code, enabling faster and smaller models
xinychen / Awesome Latex DrawingDrawing Bayesian networks, graphical models, tensors, technical frameworks, and illustrations in LaTeX.
