We write your reusable computer vision tools. 💜
Repository Index
47,133 repositories indexed
1–24 of 26 · Most stars
Ray is an AI compute engine. Ray consists of a core distributed runtime and a set of AI Libraries for accelerating ML workloads.
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.
Deezer source separation library including pretrained models.
🤗 The largest hub of ready-to-use datasets for AI models with fast, easy-to-use and efficient data manipulation tools
机器学习相关教程
The AI developer platform. Use Weights & Biases to train and fine-tune models, and manage models from experimentation to production.
Deep Learning and Reinforcement Learning Library for Scientists and Engineers
MMdnn is a set of tools to help users inter-operate among different deep learning frameworks. E.g. model conversion and visualization. Convert models between Caffe, Keras, MXNet, Tensorflow, CNTK, PyTorch Onnx and CoreML.
ZenML 🙏: One AI Platform from Pipelines to Agents. https://zenml.io.
:earth_americas: Simple and ready-to-use tutorials for TensorFlow
A best practice for tensorflow project template architecture.
[验证码识别-训练] This project is based on CNN/ResNet/DenseNet+GRU/LSTM+CTC/CrossEntropy to realize verification code identification. This project is only for training the model.
TensorFlow Recommenders is a library for building recommender system models using TensorFlow.
Upscale an image by a factor of 4, while generating photo-realistic details.
kapre: Keras Audio Preprocessors
PyTorch to Keras model convertor
Chatbot in 200 lines of code using TensorLayer
in progress
A collection of state-of-the-art algorithms for the training, serving and interpretation of Decision Forest models in Keras.
Using deep stacked residual bidirectional LSTM cells (RNN) with TensorFlow, we do Human Activity Recognition (HAR). Classifying the type of movement amongst 6 categories or 18 categories on 2 different datasets.
Learning cell communication from spatial graphs of cells
A Simple Example for Imitation Learning with Dataset Aggregation (DAGGER) on Torcs Env
Detect the sentiment captured in short pieces of text