347 Open source projects that are alternatives of or similar to Keras Cloud Ml Engine

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List of all AI related learning materials and practical tools to get started with AI apps

If you are looking to become a Google Cloud Engineer , then you are at the right place. GCPSketchnote is series where I share Google Cloud concepts in quick and easy to learn format.

Ephemeral Hadoop clusters using Google Compute Platform

Google Colaboratory background/task executioner & controller.

BigQuery data source for Apache Spark: Read data from BigQuery into DataFrames, write DataFrames into BigQuery tables.

Terraform Google Cloud Platform Beta provider

Ruby runtime for Google Cloud Platform

Run Sonatype Nexus Repository Manager OSS on top of Kubernetes (GKE). Includes instructions for automated backups (GCS) and day-to-day usage.

Serverless GCP Cloud Functions + Datastore implementation of RealWorld Backend

In this workshop, you'll learn how to install and configure Istio, an open source framework for connecting, securing, and managing microservices, on Google Kubernetes Engine, Google’s hosted Kubernetes product. You will also deploy an Istio-enabled multi-service application

Google Cloud Client Library for Java

A service proxy that provides API management capabilities using Google Service Infrastructure.

A Team Management app for creating tournaments and games for various sports

☁️ Go API for open cloud

labs guide for completing qwiklabs challenge

Clojure API for a more dynamic Google Dataflow

A curated list of dedicated resources and applications

A small convolution neural network deep learning framework implemented in c++.

Variational Autoencoder and Conditional Variational Autoencoder on MNIST in PyTorch

Simple Implementation of many GAN models with PyTorch.

Tensorflow Implementation of the paper [Neural Discrete Representation Learning](https://arxiv.org/abs/1711.00937) (VQ-VAE).

Minimalist implementation of VQ-VAE in Pytorch

A scratch implementation of Convolutional Neural Network in Python using only numpy and validated over CIFAR-10 & MNIST Dataset

Çeşitli kütüphaneler kullanılarak Türkçe kod açıklamalarıyla TEMEL SEVİYEDE pratik derin öğrenme uygulamaları.

Lingvo

MNIST with TensorFlow Lite on Android

Generative Adversarial Network for MNIST with tensorflow

Collection of generative models in Pytorch version.

MNIST classification using Convolutional NeuralNetwork. Various techniques such as data augmentation, dropout, batchnormalization, etc are implemented.

Non-negative Positive-Unlabeled (nnPU) and unbiased Positive-Unlabeled (uPU) learning reproductive code on MNIST and CIFAR10

텐서플로우를 기초부터 응용까지 단계별로 연습할 수 있는 소스 코드를 제공합니다

Tensorflow implementation of Generative Adversarial Networks (GAN) and Deep Convolutional Generative Adversarial Netwokrs for MNIST dataset.

🎎 InfoGAN: Interpretable Representation Learning

Tensorflow implementation of conditional variational auto-encoder for MNIST

This is a sample project demonstrating the use of Keras (Tensorflow) for the training of a MNIST model for handwriting recognition using CoreML on iOS 11 for inference.

Keras implementations of Generative Adversarial Networks. GANs, DCGAN, CGAN, CCGAN, WGAN and LSGAN models with MNIST and CIFAR-10 datasets.

The Pytorch Implementation of L-Softmax

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

Tensorflow implementation of conditional Generative Adversarial Networks (cGAN) and conditional Deep Convolutional Adversarial Networks (cDCGAN) for MANIST dataset.

TI-pooling: transformation-invariant pooling for feature learning in Convolutional Neural Networks

Generative Probabilistic Novelty Detection with Adversarial Autoencoders

Implement Decoupled Neural Interfaces using Synthetic Gradients in Pytorch

Tensorflow implementation of different GANs and their comparisions

Pytorch、Scikit-learn实现多种分类方法，包括逻辑回归（Logistic Regression）、多层感知机（MLP）、支持向量机（SVM）、K近邻（KNN）、CNN、RNN，极简代码适合新手小白入门，附英文实验报告（ACM模板）

Sample cloud-native application with 10 microservices showcasing Kubernetes, Istio, gRPC and OpenCensus.