Mnist Open Source Projects

TensorFlow Tutorial and Examples for Beginners (support TF v1 & v2)

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.

A set of examples around pytorch in Vision, Text, Reinforcement Learning, etc.

☁️ Build multimodal AI applications with cloud-native stack

pytorch handbook是一本开源的书籍，目标是帮助那些希望和使用PyTorch进行深度学习开发和研究的朋友快速入门，其中包含的Pytorch教程全部通过测试保证可以成功运行

A collection of various deep learning architectures, models, and tips

A MNIST-like fashion product database. Benchmark :point_down:

Deep Learning in Javascript. Train Convolutional Neural Networks (or ordinary ones) in your browser.

Keras implementations of Generative Adversarial Networks.

Examples built with TensorFlow.js

Run Keras models in the browser, with GPU support using WebGL

Collection of generative models in Tensorflow

A Tensorflow implementation of CapsNet(Capsules Net) in paper Dynamic Routing Between Capsules

This repo contains the source code in my personal column (https://zhuanlan.zhihu.com/zhaoyeyu), implemented using Python 3.6. Including Natural Language Processing and Computer Vision projects, such as text generation, machine translation, deep convolution GAN and other actual combat code.

[CVPR2020] Adversarial Latent Autoencoders

Determined is an open-source machine learning platform that simplifies distributed training, hyperparameter tuning, experiment tracking, and resource management. Works with PyTorch and TensorFlow.

Introduction to Deep Neural Networks with Keras and Tensorflow

Lingvo

Base pretrained models and datasets in pytorch (MNIST, SVHN, CIFAR10, CIFAR100, STL10, AlexNet, VGG16, VGG19, ResNet, Inception, SqueezeNet)

Algorithms for explaining machine learning models

Collection of generative models in Pytorch version.

TensorFlow Tutorials

Machine learning platform for Web developers

Machine learning lessons and teaching projects designed for engineers

텐서플로우를 기초부터 응용까지 단계별로 연습할 수 있는 소스 코드를 제공합니다

Official community-driven Azure Machine Learning examples, tested with GitHub Actions.

Advanced Deep Learning with Keras, published by Packt

Pytorch implementations of Bayes By Backprop, MC Dropout, SGLD, the Local Reparametrization Trick, KF-Laplace, SG-HMC and more

GPU Accelerated t-SNE for CUDA with Python bindings

Parallel t-SNE implementation with Python and Torch wrappers.

A PyTorch implementation of the NIPS 2017 paper "Dynamic Routing Between Capsules".

Various ipython notebooks

A pytorch implementation of Paper "Improved Training of Wasserstein GANs"

Deep Learning in Haskell

Implementation of Communication-Efficient Learning of Deep Networks from Decentralized Data

[pip install medmnist] 18x Standardized Datasets for 2D and 3D Biomedical Image Classification

Awesome-TensorFlow-Chinese，TensorFlow 中文资源精选，官方网站，安装教程，入门教程，视频教程，实战项目，学习路径。QQ群：167122861，公众号：磐创AI，微信群二维码：http://www.tensorflownews.com/

Configure Caffe in one hour for Windows users.

Early stopping for PyTorch

A neural network toolkit for Metal

Tensors and neural networks in Haskell

Videos, notes and experiments to understand deep learning

Neural network OCR.

learn code with tensorflow

Layers Outputs and Gradients in Keras. Made easy.

Datascience-Interview-Questions for Korean

Learn deep learning with tensorflow2.0, keras and python through this comprehensive deep learning tutorial series. Learn deep learning from scratch. Deep learning series for beginners. Tensorflow tutorials, tensorflow 2.0 tutorial. deep learning tutorial python.

动手学CV-Pytorch版

Vector Quantized VAEs - PyTorch Implementation

Normalizing flows in PyTorch. Current intended use is education not production.

PyTorch implementation of Deformable Convolution

Some interesting TensorFlow tutorials for beginners.

GANomaly: Semi-Supervised Anomaly Detection via Adversarial Training

Boltzmann Machines in TensorFlow with examples

AoE (AI on Edge，终端智能，边缘计算) 是一个终端侧AI集成运行时环境 (IRE)，帮助开发者提升效率。

Experiments for understanding disentanglement in VAE latent representations

Generative Adversarial Networks implemented in PyTorch and Tensorflow

Descriptive Deep Learning

Deep learning with spiking neural networks (SNNs) in PyTorch.