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    Overview
    ProductRatingMost Used ByProduct SummaryStarting Price

    TensorFlow

    Score7.6 out of 10
    N/ATensorFlow is an open-source machine learning software library for numerical computation using data flow graphs. It was originally developed by Google.N/A

    Wireshark

    Score8.9 out of 10
    N/AWireshark is a free and open source network troubleshooting tool.

    $0

    Pricing
    TensorFlowWireshark
    Editions & Modules
    No answers on this topic
    Wireshark
    Free
    Offerings
    Pricing Offerings
    TensorFlowWireshark
    Free Trial
    NoNo
    Free/Freemium Version
    NoYes
    Premium Consulting/Integration Services
    NoNo
    Entry-level Setup FeeNo setup feeNo setup fee
    Additional Details——
    More Pricing Information
    Community Pulse
    TensorFlowWireshark
    Considered Both Products
    Open Source
    No answer on this topic
    Open Source
    No answer on this topic
    Key User Insights
    Would buy again
    No answers on this topic
    100%
    Would buy again
    24 Answers
    Delivers good value for the price
    No answers on this topic
    100%
    Delivers good value for the price
    24 Answers
    Happy with the feature set
    No answers on this topic
    100%
    Happy with the feature set
    24 Answers
    Lived up to sales and marketing promises
    No answers on this topic
    100%
    Lived up to sales and marketing promises
    16 Answers
    Implementation went as expected
    No answers on this topic
    100%
    Implementation went as expected
    22 Answers
    Best Alternatives
    TensorFlowWireshark
    Small Businesses
    Google Cloud AI
    Score8.7 out of 10
    No answers on this topic
    Medium-sized Companies
    Google Cloud AI
    Score8.7 out of 10
    No answers on this topic
    Enterprises
    Google Cloud AI
    Score8.7 out of 10
    No answers on this topic
    All AlternativesView all alternativesView all alternatives
    User Ratings
    TensorFlowWireshark
    Likelihood to Recommend
    6.0
    (15 ratings)
    9.6
    (32 ratings)
    Likelihood to Renew
    -
    (0 ratings)
    10.0
    (1 ratings)
    Usability
    9.0
    (1 ratings)
    10.0
    (3 ratings)
    Support Rating
    9.1
    (2 ratings)
    10.0
    (3 ratings)
    Implementation Rating
    8.0
    (1 ratings)
    10.0
    (1 ratings)
    User Testimonials
    TensorFlowWireshark
    Likelihood to Recommend
    Open Source
    TensorFlow is great for most deep learning purposes. This is especially true in two domains: 1. Computer vision: image classification, object detection and image generation via generative adversarial networks 2. Natural language processing: text classification and generation. The good community support often means that a lot of off-the-shelf models can be used to prove a concept or test an idea quickly. That, and Google's promotion of Colab means that ideas can be shared quite freely. Training, visualizing and debugging models is very easy in TensorFlow, compared to other platforms (especially the good old Caffe days). In terms of productionizing, it's a bit of a mixed bag. In our case, most of our feature building is performed via Apache Spark. This means having to convert Parquet (columnar optimized) files to a TensorFlow friendly format i.e., protobufs. The lack of good JVM bindings mean that our projects end up being a mix of Python and Scala. This makes it hard to reuse some of the tooling and support we wrote in Scala. This is where MXNet shines better (though its Scala API could do with more work).
    Incentivized
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    Open Source
    I don't know of any other tool that works as well as Wireshark for packet capture an inspection. It's extremely easy to get up and running, and even with little to no knowledge of how to use the tool, you can be looking at all the traffic coming off a network interface.
    Incentivized
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    Pros
    Open Source
    • A vast library of functions for all kinds of tasks - Text, Images, Tabular, Video etc.
    • Amazing community helps developers obtain knowledge faster and get unblocked in this active development space.
    • Integration of high-level libraries like Keras and Estimators make it really simple for a beginner to get started with neural network based models.
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    Open Source
    • Light-weight software - Does not require high end specifications; also runs smoothly on Legacy systems
    • Filter function - Lets you filter you packets from thousands to tens so as to find your target much easily
    • Simultaneous capturing on all the network adapters - You can capture packets from all the Network Interface Cards (NIC's) at once.
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    Cons
    Open Source
    • RNNs are still a bit lacking, compared to Theano.
    • Cannot handle sequence inputs
    • Theano is perhaps a bit faster and eats up less memory than TensorFlow on a given GPU, perhaps due to element-wise ops. Tensorflow wins for multi-GPU and “compilation” time.
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    Open Source
    • A more user-friendly interface would be nice, but then again it is not really designed for those who are not quite comfortable with this type of software.
    • Changes to functionality on updates - this can sometimes happen unexpectedly and can be an annoyance.
    • More powerful data processing would be welcomed
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    Usability
    Open Source
    Support of multiple components and ease of development.
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    Open Source
    It's very simple and easy to use, although individuals not used to managing and administering networks would take some time to get familiar with it. Once they have mastered use of the application, it's easy to stay knowledgeable about it, iteration after iteration. It is well supported online through an open-source community network of professionals who are helpful in imparting knowledge and in providing assistance.
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    Support Rating
    Open Source
    Community support for TensorFlow is great. There's a huge community that truly loves the platform and there are many examples of development in TensorFlow. Often, when a new good technique is published, there will be a TensorFlow implementation not long after. This makes it quick to ally the latest techniques from academia straight to production-grade systems. Tooling around TensorFlow is also good. TensorBoard has been such a useful tool, I can't imagine how hard it would be to debug a deep neural network gone wrong without TensorBoard.
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    Open Source
    I don't believe Wireshark has "true" support as the software is open source. However, there is an active & friendly community around Wireshark that are more than happy to help answer questions. From a comprehensive Wiki and FAQ section on the site to the Ask a Question forum and bug tracker section, there's plenty of support options to make sure your questions and issues are addressed.
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    Implementation Rating
    Open Source
    Use of cloud for better execution power is recommended.
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    Open Source
    Simple and easy setup.
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    Alternatives Considered
    Open Source
    Keras is built on top of TensorFlow, but it is much simpler to use and more Python style friendly, so if you don't want to focus on too many details or control and not focus on some advanced features, Keras is one of the best options, but as far as if you want to dig into more, for sure TensorFlow is the right choice
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    Open Source
    Wireshark is a free tool that came highly recommended by one of our former network security consultants. Using the tool he was able to resolve all of our higher tier network tickets, so we observed first hand why we needed to add Wireshark into our toolset. We received in-depth instruction and training scenarios that demonstrated the effectiveness and power of the product, so we didn't spend any time reviewing competing products.
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    Return on Investment
    Open Source
    • Learning is s bit difficult takes lot of time.
    • Developing or implementing the whole neural network is time consuming with this, as you have to write everything.
    • Once you have learned this, it make your job very easy of getting the good result.
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    Open Source
    • Identifying bugs in the network has never been smooth and near-perfect.
    • Wireshark has made sure our equipment and software is working properly via analyzing network data.
    • Analysis of IP packets and Sip call flaws has saved us a lot of time and confident result.
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