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Amazon Machine Learning
Amazon Machine Learning

83
108
+ 1
0
Wombat
Wombat

2
11
+ 1
11
Yola
Yola

4
8
+ 1
0
- No public GitHub repository available -
- No public GitHub repository available -
- No public GitHub repository available -

What is Amazon Machine Learning?

This new AWS service helps you to use all of that data you鈥檝e 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鈥檛 have an advanced degree in statistics or the desire to setup, run, and maintain your own processing and storage infrastructure.

What is Wombat?

Automate your store in no time: Wombat is an ecommerce integration platform that quickly connects your storefront with all your favorite 3rd party services. Comprehensive enough for large ecommerce stores and easy enough for small merchants

What is Yola?

Yola (formerly known as Synthasite) is a browser based Ajax website creator with an extra collaboration enabling feature. Yola lets you create your own website with WYSIWYG editing and drag and drop multimedia features. There are also drag and drop HTML and plain text fields, labels and images. Yola also offers file management, component libraries, template libraries and hosting.
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                  What are some alternatives to Amazon Machine Learning, Wombat, and Yola?
                  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.
                  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.
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                  Decisions about Amazon Machine Learning, Wombat, and Yola
                  Julien DeFrance
                  Julien DeFrance
                  Principal Software Engineer at Tophatter | 2 upvotes 24.5K views
                  atSmartZipSmartZip
                  Serverless
                  Serverless
                  AWS Lambda
                  AWS Lambda
                  Amazon Machine Learning
                  Amazon Machine Learning
                  Amazon SageMaker
                  Amazon SageMaker
                  #PaaS
                  #GCP
                  #FaaS

                  Which #IaaS / #PaaS to chose? Not all #Cloud providers are created equal. As you start to use one or the other, you'll build around very specific services that don't have their equivalent elsewhere.

                  Back in 2014/2015, this decision I made for SmartZip was a no-brainer and #AWS won. AWS has been a leader, and over the years demonstrated their capacity to innovate, and reducing toil. Like no other.

                  Year after year, this kept on being confirmed, as they rolled out new (managed) services, got into Serverless with AWS Lambda / FaaS And allowed domains such as #AI / #MachineLearning to be put into the hands of every developers thanks to Amazon Machine Learning or Amazon SageMaker for instance.

                  Should you compare with #GCP for instance, it's not quite there yet. Building around these managed services, #AWS allowed me to get my developers on a whole new level. Where they know what's under the hood. Where they know they have these services available and can build around them. Where they care and are responsible for operations and security and deployment of what they've worked on.

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                  How developers use Amazon Machine Learning, Wombat, and Yola
                  Avatar of Taylor Host
                  Taylor Host uses Amazon Machine LearningAmazon Machine Learning

                  Mild re-training data usage.

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