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Pros of Azure Machine Learning
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Pros of NanoNets
- Simple API7
- Easy Setup5
- Easy to use4
- Fast Training3
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What is Amazon Machine Learning?
This new AWS service helps you to use all of that data you’ve been collecting to improve the quality of your decisions. You can build and fine-tune predictive models using large amounts of data, and then use Amazon Machine Learning to make predictions (in batch mode or in real-time) at scale. You can benefit from machine learning even if you don’t have an advanced degree in statistics or the desire to setup, run, and maintain your own processing and storage infrastructure.
What is Azure Machine Learning?
Azure Machine Learning is a fully-managed cloud service that enables data scientists and developers to efficiently embed predictive analytics into their applications, helping organizations use massive data sets and bring all the benefits of the cloud to machine learning.
What is 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.
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What tools integrate with Amazon Machine Learning?
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What tools integrate with Amazon Machine Learning?
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What are some alternatives to Amazon Machine Learning, Azure Machine Learning, and NanoNets?
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.
Apache Spark
Spark is a fast and general processing engine compatible with Hadoop data. It can run in Hadoop clusters through YARN or Spark's standalone mode, and it can process data in HDFS, HBase, Cassandra, Hive, and any Hadoop InputFormat. It is designed to perform both batch processing (similar to MapReduce) and new workloads like streaming, interactive queries, and machine learning.
Amazon SageMaker
A fully-managed service that enables developers and data scientists to quickly and easily build, train, and deploy machine learning models at any scale.
RapidMiner
It is a software platform for data science teams that unites data prep, machine learning, and predictive model deployment.
Google AI Platform
Makes it easy for machine learning developers, data scientists, and data engineers to take their ML projects from ideation to production and deployment, quickly and cost-effectively.