There are 398 repositories under keras topic.
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.
Mask R-CNN for object detection and instance segmentation on Keras and TensorFlow
Visualizer for neural network, deep learning, and machine learning models
100-Days-Of-ML-Code中文版
Interactive deep learning book with multi-framework code, math, and discussions. Adopted at 400 universities from 60 countries including Stanford, MIT, Harvard, and Cambridge.
ncnn is a high-performance neural network inference framework optimized for the mobile platform
Essential Cheat Sheets for deep learning and machine learning researchers https://medium.com/@kailashahirwar/essential-cheat-sheets-for-machine-learning-and-deep-learning-researchers-efb6a8ebd2e5
A neural network that transforms a design mock-up into a static website.
🏆 A ranked list of awesome machine learning Python libraries. Updated weekly.
Keras implementations of Generative Adversarial Networks.
AutoML library for deep learning
Deep learning operations reinvented (for pytorch, tensorflow, jax and others)
A Deep-Learning-Based Chinese Speech Recognition System 基于深度学习的中文语音识别系统
Techniques for deep learning with satellite & aerial imagery
人工智能学习路线图,整理近200个实战案例与项目,免费提供配套教材,零基础入门,就业实战!包括:Python,数学,机器学习,数据分析,深度学习,计算机视觉,自然语言处理,PyTorch tensorflow machine-learning,deep-learning data-analysis data-mining mathematics data-science artificial-intelligence python tensorflow tensorflow2 caffe keras pytorch algorithm numpy pandas matplotlib seaborn nlp cv等热门领域
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.
🔥 A tool for visualizing and tracking your machine learning experiments. This repo contains the CLI and Python API.
A course in reinforcement learning in the wild
Washington University (in St. Louis) Course T81-558: Applications of Deep Neural Networks
Run Keras models in the browser, with GPU support using WebGL
Easily train your own text-generating neural network of any size and complexity on any text dataset with a few lines of code.
Neural network 3D visualization framework, build interactive and intuitive model in browsers, support pre-trained deep learning models from TensorFlow, Keras, TensorFlow.js
Keras model to generate HTML code from hand-drawn website mockups. Implements an image captioning architecture to drawn source images.
TensorFlow Basic Tutorial Labs
Segmentation models with pretrained backbones. Keras and TensorFlow Keras.
Fast, distributed, secure AI for Big Data
PipelineAI Kubeflow Distribution
🔎 Super-scale your images and run experiments with Residual Dense and Adversarial Networks.
In this repository, I will share some useful notes and references about deploying deep learning-based models in production.