There are 433 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.
Visualizer for neural network, deep learning and machine learning models
Mask R-CNN for object detection and instance segmentation on Keras and TensorFlow
100-Days-Of-ML-Code中文版
A neural network that transforms a design mock-up into a static website.
🏆 A ranked list of awesome machine learning Python libraries. Updated weekly.
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
Keras implementations of Generative Adversarial Networks.
AutoML library for deep learning
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
Flexible and powerful tensor operations for readable and reliable code (for pytorch, jax, TF and others)
Techniques for deep learning with satellite & aerial imagery
A Deep-Learning-Based Chinese Speech Recognition System 基于深度学习的中文语音识别系统
A course in reinforcement learning in the wild
T81-558: Keras - Applications of Deep Neural Networks @Washington University in St. Louis
Keras model to generate HTML code from hand-drawn website mockups. Implements an image captioning architecture to drawn source images.
Neural network 3D visualization framework, build interactive and intuitive model in browsers, support pre-trained deep learning models from TensorFlow, Keras, TensorFlow.js
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.
Accelerate local LLM inference and finetuning (LLaMA, Mistral, ChatGLM, Qwen, Baichuan, Mixtral, Gemma, etc.) on Intel CPU and GPU (e.g., local PC with iGPU, discrete GPU such as Arc, Flex and Max). A PyTorch LLM library that seamlessly integrates with llama.cpp, HuggingFace, LangChain, LlamaIndex, DeepSpeed, vLLM, FastChat, ModelScope, etc.
Segmentation models with pretrained backbones. Keras and TensorFlow Keras.
A comprehensive machine learning repository containing 30+ notebooks on different concepts, algorithms and techniques.
🔎 Super-scale your images and run experiments with Residual Dense and Adversarial Networks.
TensorFlow Basic Tutorial Labs
In this repository, I will share some useful notes and references about deploying deep learning-based models in production.