Learn how to develop, deploy and iterate on production-grade ML applications.
Visualizer for neural network, deep learning and machine learning models
:zap: A Fast, Extensible Progress Bar for Python and CLI
Data science Python notebooks: Deep learning (TensorFlow, Theano, Caffe, Keras), scikit-learn, Kaggle, big data (Spark, Hadoop MapReduce, HDFS), matpl...
Interactive deep learning book with multi-framework code, math, and discussions. Adopted at 500 universities from 70 countries including Stanford, MIT...
Mask R-CNN for object detection and instance segmentation on Keras and TensorFlow
🏆 A ranked list of awesome machine learning Python libraries. Updated weekly.
ncnn is a high-performance neural network inference framework optimized for the mobile platform
A Lightweight Face Recognition and Facial Attribute Analysis (Age, Gender, Emotion and Race) Library for Python
100-Days-Of-ML-Code中文版
Open standard for machine learning interoperability
A neural network that transforms a design mock-up into a static website.
Essential Cheat Sheets for deep learning and machine learning researchers https://medium.com/@kailashahirwar/essential-cheat-sheets-for-machine-learni...
Distributed training framework for TensorFlow, Keras, PyTorch, and Apache MXNet.
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,...
一款入门级的人脸、视频、文字检测以及识别的项目.
The AI developer platform. Use Weights & Biases to train and fine-tune models, and manage models from experimentation to production.
Techniques for deep learning with satellite & aerial imagery
Flexible and powerful tensor operations for readable and reliable code (for pytorch, jax, TF and others)
AutoML library for deep learning
Keras implementations of Generative Adversarial Networks.
A Deep-Learning-Based Chinese Speech Recognition System 基于深度学习的中文语音识别系统
An open source library for deep learning end-to-end dialog systems and chatbots.
A course in reinforcement learning in the wild
Setup and customize deep learning environment in seconds.
Aim 💫 — An easy-to-use & supercharged open-source experiment tracker.
MMdnn is a set of tools to help users inter-operate among different deep learning frameworks. E.g. model conversion and visualization. Convert models...
T81-558: Keras - Applications of Deep Neural Networks @Washington University in St. Louis
Deep Reinforcement Learning for Keras.
股票AI操盘手:从学习、模拟到实盘,一站式平台。包含股票知识、策略实例、大模型、因子挖掘、传统策略、机器学习、深度学习、强化学习、图网络、高频交易、C++...
Tools to Design or Visualize Architecture of Neural Network
Neural network 3D visualization framework, build interactive and intuitive model in browsers, support pre-trained deep learning models from TensorFlow...
Keras model to generate HTML code from hand-drawn website mockups. Implements an image captioning architecture to drawn source images.
A comprehensive machine learning repository containing 30+ notebooks on different concepts, algorithms and techniques.
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.
Segmentation models with pretrained backbones. Keras and TensorFlow Keras.
unet for image segmentation
🔎 Super-scale your images and run experiments with Residual Dense and Adversarial Networks.
TensorFlow Basic Tutorial Labs
A clean implementation based on AlphaZero for any game in any framework + tutorial + Othello/Gobang/TicTacToe/Connect4 and more
In this repository, I will share some useful notes and references about deploying deep learning-based models in production.
Fast, distributed, secure AI for Big Data
PipelineAI
A repository for storing models that have been inter-converted between various frameworks. Supported frameworks are TensorFlow, PyTorch, ONNX, OpenVIN...
Model summary in PyTorch similar to `model.summary()` in Keras
A comprehensive list of Deep Learning / Artificial Intelligence and Machine Learning tutorials - rapidly expanding into areas of AI/Deep Learning / Ma...
A high performance and generic framework for distributed DNN training
MLOps Tools For Managing & Orchestrating The Machine Learning LifeCycle
🧠💬 Articles I wrote about machine learning, archived from MachineCurve.com.