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  5. Amazon Personalize vs Dasha

Amazon Personalize vs Dasha

OverviewComparisonAlternatives

Overview

Amazon Personalize
Amazon Personalize
Stacks20
Followers62
Votes0
Dasha
Dasha
Stacks3
Followers8
Votes0

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Detailed Comparison

Amazon Personalize
Amazon Personalize
Dasha
Dasha

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

Dasha is a conversational AI as a Service platform. Dasha lets you create conversational apps that are more human-like than ever before, quicker than ever before and quickly integrate them into your products.

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;
Declarative language for conversation design; VSCode extension; native STT, NLP, NLU, NLG and TTS; Support for external TTS; Voice over SIP Trunk; Node.js SDK; Voice over GRPC; Text over GRPC; API-first; Open developer platform; Unlimited conversational depth; High conversational concurrency; Robust digressions and intents for the human-like experience; Custom intents training
Statistics
Stacks
20
Stacks
3
Followers
62
Followers
8
Votes
0
Votes
0
Integrations
No integrations available
Node.js
Node.js
Visual Studio Code
Visual Studio Code

What are some alternatives to Amazon Personalize, Dasha?

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.

rasa NLU

rasa NLU

rasa NLU (Natural Language Understanding) is a tool for intent classification and entity extraction. You can think of rasa NLU as a set of high level APIs for building your own language parser using existing NLP and ML libraries.

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

SpaCy

SpaCy

It is a library for advanced Natural Language Processing in Python and Cython. It's built on the very latest research, and was designed from day one to be used in real products. It comes with pre-trained statistical models and word vectors, and currently supports tokenization for 49+ languages.

Polyaxon

Polyaxon

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

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