Add to ORKGDistributed Machine Learning (DML) has recently become popular and Parameter Server is an easy to use and efficient framework to solve DML problems. Setting up and configuring Parameter Server are challenges to data analytics and researchers with focusing in training and testing their models. We implement a cloud web applications to integrate with an Auto Deployment Platform for Parameter Server along with a Benchmark as references. The cloud web system includes a back-end system to deal with integration and scale problems, and a cross-platform web responsive front-end interacts with end-users. To demonstrate the implementation of our web applications, we go through from client interface implementations to database, back-end API and fin...
National audienceFederated Learning (FL) is a new area of distributed Machine Learning (ML) that eme...
Cloud service providers give users resources as service products through the internet. Using cloud s...
Abstract—This paper presents a new model of mobile distance learning system (MDL) in an extended mob...
Distributed Machine Learning (DML) was introduced as a solution to solve the current big data proble...
Today, machine learning is not something strange anymore. The application of machine learning is nea...
The thesis consists of a full-stack web service application: the client-side application written wit...
Machine learning (ML) is prevalent in today’s world. Starting from the need to improve artificial in...
In this paper we propose a distributed architecture to provide machine learning practitioners with a...
Training large, complex machine learning models such as deep neural networks with big data requires ...
The delegation of resource-intensive operations to the server-side computers is an ongoing trend. Co...
With the rise of Internet of Things, cloud computing has become an increasingly important concept. A...
This paper presents a general overview of how machine learning solutions may be implemented using mo...
The advent of algorithms capable of leveraging vast quantities of data and computational resources h...
The advent of algorithms capable of leveraging vast quantities of data and computational resources h...
In this paper we propose a distributed architecture to provide machine learning practitioners with a...
National audienceFederated Learning (FL) is a new area of distributed Machine Learning (ML) that eme...
Cloud service providers give users resources as service products through the internet. Using cloud s...
Abstract—This paper presents a new model of mobile distance learning system (MDL) in an extended mob...
Distributed Machine Learning (DML) was introduced as a solution to solve the current big data proble...
Today, machine learning is not something strange anymore. The application of machine learning is nea...
The thesis consists of a full-stack web service application: the client-side application written wit...
Machine learning (ML) is prevalent in today’s world. Starting from the need to improve artificial in...
In this paper we propose a distributed architecture to provide machine learning practitioners with a...
Training large, complex machine learning models such as deep neural networks with big data requires ...
The delegation of resource-intensive operations to the server-side computers is an ongoing trend. Co...
With the rise of Internet of Things, cloud computing has become an increasingly important concept. A...
This paper presents a general overview of how machine learning solutions may be implemented using mo...
The advent of algorithms capable of leveraging vast quantities of data and computational resources h...
The advent of algorithms capable of leveraging vast quantities of data and computational resources h...
In this paper we propose a distributed architecture to provide machine learning practitioners with a...
National audienceFederated Learning (FL) is a new area of distributed Machine Learning (ML) that eme...
Cloud service providers give users resources as service products through the internet. Using cloud s...
Abstract—This paper presents a new model of mobile distance learning system (MDL) in an extended mob...