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  5. Amazon Personalize vs Gorse

Amazon Personalize vs Gorse

OverviewComparisonAlternatives

Overview

Amazon Personalize
Amazon Personalize
Stacks20
Followers62
Votes0
Gorse
Gorse
Stacks1
Followers2
Votes0
GitHub Stars6
Forks0

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Detailed Comparison

Amazon Personalize
Amazon Personalize
Gorse
Gorse

Machine learning service that makes it easy for developers to add individualized recommendations to customers using their applications.

It is an open-source recommendation system written in Go. It aims to be an universal open-source recommender system that can be quickly introduced into a wide variety of online services. By importing items, users and interaction data into Gorse, the system will automatically train models to generate recommendations for each user.

Combine customer and contextual data to generate high-quality recommendations; Automated machine learning; Continuous learning to improve performance; Bring your own algorithms; Easily integrate with your existing tools;
Choose the best recommendation model and strategy automatically by model searching in the background; Single node training, distributed prediction, and ability to achieve horizontal scaling in the recommendation stage; Provide RESTful APIs for data CRUD and recommendation requests; Provide dashboard for data import and export, monitoring, and cluster status checking
Statistics
GitHub Stars
-
GitHub Stars
6
GitHub Forks
-
GitHub Forks
0
Stacks
20
Stacks
1
Followers
62
Followers
2
Votes
0
Votes
0
Integrations
No integrations available
Golang
Golang
MySQL
MySQL
Redis
Redis
MongoDB
MongoDB
Docker Compose
Docker Compose

What are some alternatives to Amazon Personalize, Gorse?

TensorFlow

TensorFlow

TensorFlow is an open source software library for numerical computation using data flow graphs. Nodes in the graph represent mathematical operations, while the graph edges represent the multidimensional data arrays (tensors) communicated between them. The flexible architecture allows you to deploy computation to one or more CPUs or GPUs in a desktop, server, or mobile device with a single API.

scikit-learn

scikit-learn

scikit-learn is a Python module for machine learning built on top of SciPy and distributed under the 3-Clause BSD license.

PyTorch

PyTorch

PyTorch is not a Python binding into a monolothic C++ framework. It is built to be deeply integrated into Python. You can use it naturally like you would use numpy / scipy / scikit-learn etc.

Keras

Keras

Deep Learning library for Python. Convnets, recurrent neural networks, and more. Runs on TensorFlow or Theano. https://keras.io/

NanoNets

NanoNets

Build a custom machine learning model without expertise or large amount of data. Just go to nanonets, upload images, wait for few minutes and integrate nanonets API to your application.

Kubeflow

Kubeflow

The Kubeflow project is dedicated to making Machine Learning on Kubernetes easy, portable and scalable by providing a straightforward way for spinning up best of breed OSS solutions.

TensorFlow.js

TensorFlow.js

Use flexible and intuitive APIs to build and train models from scratch using the low-level JavaScript linear algebra library or the high-level layers API

Polyaxon

Polyaxon

An enterprise-grade open source platform for building, training, and monitoring large scale deep learning applications.

Streamlit

Streamlit

It is the app framework specifically for Machine Learning and Data Science teams. You can rapidly build the tools you need. Build apps in a dozen lines of Python with a simple API.

Inferrd

Inferrd

It is the easiest way to deploy Machine Learning models. Start deploying Tensorflow, Scikit, Keras and spaCy straight from your notebook with just one extra line.

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