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Amazon Machine Learning vs TensorFlow: What are the differences?

Amazon Machine Learning: Visualization tools and wizards that guide you through the process of creating ML models w/o having to learn complex ML algorithms & technology. 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; TensorFlow: Open Source Software Library for Machine Intelligence. 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.

Amazon Machine Learning belongs to "Machine Learning as a Service" category of the tech stack, while TensorFlow can be primarily classified under "Machine Learning Tools".

Uber Technologies, 9GAG, and Postmates are some of the popular companies that use TensorFlow, whereas Amazon Machine Learning is used by Apli, Cymatic Security, and FetchyFox. TensorFlow has a broader approval, being mentioned in 200 company stacks & 135 developers stacks; compared to Amazon Machine Learning, which is listed in 9 company stacks and 10 developer stacks.

Advice on Amazon Machine Learning and TensorFlow

Hello everyone,

I am currently on an internship, and I am a new intern in an SME. My first mission is to choose the right tool for predictive sales analysis (management of the quantity in stock). I found several tools (paying and open source), and the company leaves the choice of tools to me (even paying). They suggest SAP Analytics Cloud as a first attempt (since we want a tool on the cloud too). I would like to have your proposals since I'm new to the business.

PS: I code in Python !! thank you in advance.

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Replies (3)
Nutchanon Ninyawee

In sales analysis, you might need some sort of timeseries prediction. I would recommend the sagemaker DeepAR. where you could co-op the seasonal effect into the model.

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philippe thiran
Research & Technology & Innovation | Software & Data & Cloud | Professor in Computer Science · | 3 upvotes · 3.4K views

Hello Amina, You need first to clearly identify the input data type (e.g. temporal data or not? seasonality or not?) and the analysis type (e.g., time series?, categories?, etc.). If you can answer these questions, that would be easier to help you identify the right tools (or Python libraries). If time series and Python, you have choice between Pendas/Statsmodels/Serima(x) (if seasonality) or deep learning techniques with Keras.

Good work, Philippe

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If you want to code it yourself and based on your desired output. RNN (Recurrent neural network) would be the right choice. You can code it using Tensorflow and use LSTM as the layers.

If you prefer on cloud with tools ready to use and not much coding, Amazon DeepAR Forecasting looks sufficient.

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Pros of Amazon Machine Learning
Pros of TensorFlow
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    • 26
      High Performance
    • 16
      Connect Research and Production
    • 13
      Deep Flexibility
    • 9
      Auto-Differentiation
    • 9
      True Portability
    • 3
      High level abstraction
    • 2
      Powerful
    • 2
      Easy to use

    Sign up to add or upvote prosMake informed product decisions

    Cons of Amazon Machine Learning
    Cons of TensorFlow
      Be the first to leave a con
      • 9
        Hard
      • 6
        Hard to debug
      • 1
        Documentation not very helpful

      Sign up to add or upvote consMake informed product decisions

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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 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.

      Need advice about which tool to choose?Ask the StackShare community!

      What companies use Amazon Machine Learning?
      What companies use TensorFlow?
      See which teams inside your own company are using Amazon Machine Learning or TensorFlow.
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      What tools integrate with Amazon Machine Learning?
      What tools integrate with TensorFlow?
        No integrations found

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        What are some alternatives to Amazon Machine Learning and TensorFlow?
        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.
        Algorithms.io
        Build And Run Predictive Applications For Streaming Data From Applications, Devices, Machines and Wearables
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