Caffe vs TensorFlow comparison

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Caffe Logo
262 views|190 comparisons
100% willing to recommend
TensorFlow Logo
6,217 views|3,852 comparisons
100% willing to recommend
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Executive Summary

We performed a comparison between Caffe and TensorFlow based on real PeerSpot user reviews.

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Quotes From Members
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Here are some excerpts of what they said:
Pros
"Caffe has helped our company become up-to-date in the market and has helped us speed up the development process of our projects."

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"TensorFlow is a framework that makes it really easy to use for deep learning.""Our clients were not aware they were using TensorFlow, so that aspect was transparent. I think we personally chose TensorFlow because it provided us with more of the end-to-end package that you can use for all the steps regarding billing and our models. So basically data processing, training the model, evaluating the model, updating the model, deploying the model and all of these steps without having to change to a new environment.""It empowers us to seamlessly create and deploy machine learning models, offering a versatile solution for implementing sophisticated environments and various types of AI solutions.""It's got quite a big community, which is useful.""It provides us with 35 features like patch normalization layers, and it is easy to implement using the Kras library when the Kaspersky flow is running behind it.""The most valuable features are the frameworks and the functionality to work with different data, even when we have a certain quantity of data flowing.""Google is behind TensorFlow, and they provide excellent documentation. It's very thorough and very helpful.""It is also totally Open-Source and free. Open-source applications are not good usually. but TensorFlow actually changed my view about it and I thought, "Look, Oh my God. This is an open-source application and it's as good as it could be." I learned that TensorFlow, by sharing their own knowledge and their own platform with other developers, it improved the lives of many people around the globe."

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Cons
"The concept of Caffe is a little bit complex because it was developed and based in C++. They need to make it easier for a new developer, data scientist, or a new machine or deep learning engineer to understand it."

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"However, if I want to change just one thing in the implementation of TensorFlow functions I have to copy everything that they wrote and I change it manually if indeed it can be amended. This is really hard as it's written in C++ and has a lot of complications.""It would be nice to have more pre-trained models that we can utilize within layers. I utilize a Mac, and I am unable to utilize AMD GPUs. That's something that I would definitely be like to be able to access within TensorFlow since most of it is with CUDA ML. This only matters for local machines because, in Azure, you can just access any GPU you want from the cloud. It doesn't really matter, but the clients that I work with don't have cloud accounts, or they don't want to utilize that or spend the money. They all see it as too expensive and want to know what they can do on their local machines.""It would be nice if the solution was in Hungarian. I would like more Hungarian NAT models.""TensorFlow Lite only outputs to C.""It doesn't allow for fast the proto-typing. So usually when we do proto-typing we will start with PyTorch and then once we have a good model that we trust, we convert it into TensorFlow. So definitely, TensorFlow is not very flexible.""It would be cool if TensorFlow could make it easier for companies like us to program for running it across different hyperscalers.""JavaScript is a different thing and all the websites and web apps and all the mobile apps are built-in JavaScript. JavaScript is the core of that. However, TensorFlow is like a machine learning item. What can be improved with TensorFlow is how it can mix in how the JavaScript developers can use TensorFlow.""Personally, I find it to be a bit too much AI-oriented."

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Pricing and Cost Advice
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  • "TensorFlow is free."
  • "I think for learners to deploy a project, you can actually use TensorFlow for free. It's just amazing to have an open-source platform like TensorFlow to deploy your own project. Here in Russia no one really cares about licenses, as it is totally open source and free. My clients in the United States were also pleased to learn when they enquired, that licensing is free."
  • "We are using the free version."
  • "It is open-source software. You don't have to pay all the big bucks like Azure and Databricks."
  • "I did not require a license for this solution. It a free open-source solution."
  • "I am using the open-source version of TensorFlow and it is free."
  • "I rate TensorFlow's pricing a five out of ten."
  • "It is an open-source solution, so anyone can use it free of charge."
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    Top Answer:It empowers us to seamlessly create and deploy machine learning models, offering a versatile solution for implementing sophisticated environments and various types of AI solutions.
    Top Answer:It is an open-source solution, so anyone can use it free of charge.
    Top Answer:The versatility of the concept is undeniable, but it can pose a challenge for developers unfamiliar with machine learning. For newcomers to the field, the learning curve can be steep, often requiring… more »
    Ranking
    17th
    Views
    262
    Comparisons
    190
    Reviews
    0
    Average Words per Review
    0
    Rating
    N/A
    4th
    Views
    6,217
    Comparisons
    3,852
    Reviews
    7
    Average Words per Review
    534
    Rating
    9.0
    Comparisons
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    Overview

    Caffe is a deep learning framework made with expression, speed, and modularity in mind. It is developed by Berkeley AI Research (BAIR) and by community contributors.

    TensorFlow is an open source software library for high performance numerical computation. Its flexible architecture allows easy deployment of computation across a variety of platforms (CPUs, GPUs, TPUs), and from desktops to clusters of servers to mobile and edge devices. Originally developed by researchers and engineers from the Google Brain team within Google’s AI organization, it comes with strong support for machine learning and deep learning and the flexible numerical computation core is used across many other scientific domains.

    Sample Customers
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    Airbnb, NVIDIA, Twitter, Google, Dropbox, Intel, SAP, eBay, Uber, Coca-Cola, Qualcomm
    Top Industries
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    VISITORS READING REVIEWS
    Manufacturing Company14%
    Computer Software Company12%
    Educational Organization11%
    University9%
    Company Size
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    REVIEWERS
    Small Business57%
    Midsize Enterprise21%
    Large Enterprise21%
    VISITORS READING REVIEWS
    Small Business21%
    Midsize Enterprise15%
    Large Enterprise64%
    Buyer's Guide
    AI Development Platforms
    May 2024
    Find out what your peers are saying about Microsoft, Google, TensorFlow and others in AI Development Platforms. Updated: May 2024.
    772,649 professionals have used our research since 2012.

    Caffe is ranked 17th in AI Development Platforms while TensorFlow is ranked 4th in AI Development Platforms with 16 reviews. Caffe is rated 7.0, while TensorFlow is rated 9.0. The top reviewer of Caffe writes "Speeds up the development process but needs to evolve more to stay relevant". On the other hand, the top reviewer of TensorFlow writes "Effective deep learning, free to use, and highly stable". Caffe is most compared with PyTorch, whereas TensorFlow is most compared with Microsoft Azure Machine Learning Studio, Google Vertex AI, OpenVINO, Hugging Face and Azure OpenAI.

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