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Probe.ly VS TensorFlow

Compare Probe.ly VS TensorFlow and see what are their differences

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Probe.ly logo Probe.ly

Intuitive and easy-to-use webapp vulnerability scanner

TensorFlow logo TensorFlow

TensorFlow is an open-source machine learning framework designed and published by Google. It tracks data flow graphs over time. Nodes in the data flow graphs represent machine learning algorithms. Read more about TensorFlow.
  • Probe.ly Landing page
    Landing page //
    2023-03-27
  • TensorFlow Landing page
    Landing page //
    2023-06-19

Probe.ly features and specs

  • User-Friendly Interface
    Probe.ly offers an intuitive and easy-to-navigate interface that makes it accessible for users of all skill levels, which reduces the learning curve and increases usability.
  • Automation
    The platform provides automated vulnerability scanning, which can save time and resources by consistently monitoring for security issues without requiring manual intervention.
  • Comprehensive Reporting
    Probe.ly generates detailed reports that help users understand vulnerabilities, their impact, and potential mitigation strategies, aiding in efficient risk management.
  • Integration with DevOps Tools
    Probe.ly integrates well with a variety of DevOps tools and CI/CD pipelines, allowing for seamless vulnerability management within existing workflows.
  • Customizable Scan Settings
    The platform allows users to customize scanning parameters and schedules, providing flexibility to target specific areas of interest or operate within defined timeframes.

Possible disadvantages of Probe.ly

  • Pricing
    Probe.ly's pricing structure might be on the higher side for small businesses or individual users, potentially limiting accessibility for smaller organizations.
  • False Positives
    As with many automated security tools, Probe.ly can sometimes generate false positives, requiring additional time and manual effort to verify real vulnerabilities.
  • Limited Language Support
    Probe.ly may have limited language support, which could be a barrier for non-English-speaking users or international teams requiring diverse linguistic options.
  • Scope Limitations
    The platform may have limitations in terms of scanning scope, such as difficulties with complex or highly dynamic web applications, potentially leading to incomplete vulnerability assessments.
  • Support Availability
    Customer support options might be limited or slower compared to larger competitors, potentially impacting resolution times for issues or queries.

TensorFlow features and specs

  • Comprehensive Ecosystem
    TensorFlow offers a complete ecosystem for end-to-end machine learning, covering everything from data preprocessing, model building, training, and deployment to production.
  • Community and Support
    TensorFlow boasts a large and active community, as well as extensive documentation and tutorials, making it easier for beginners to learn and experts to get help.
  • Flexibility
    TensorFlow supports a wide range of platforms such as CPUs, GPUs, TPUs, mobile devices, and embedded systems, providing flexibility depending on the user's needs.
  • Integrations
    TensorFlow integrates well with other Google products and services, including Google Cloud, facilitating seamless deployment and scaling.
  • Versatility
    TensorFlow can be used for a wide range of applications from simple neural networks to more complex projects, including deep learning and artificial intelligence research.

Possible disadvantages of TensorFlow

  • Complexity
    TensorFlow can be challenging to learn due to its complexity and the steep learning curve, particularly for beginners.
  • Performance Overhead
    Although TensorFlow is powerful, it can sometimes exhibit performance overhead compared to other, lighter frameworks, leading to longer training times.
  • Verbose Syntax
    The code in TensorFlow tends to be more verbose and less intuitive, which can make writing and debugging code more cumbersome relative to other frameworks like PyTorch.
  • Compatibility Issues
    Frequent updates and changes can lead to compatibility issues, requiring significant effort to keep libraries and dependencies up to date.
  • Mobile Deployment
    While TensorFlow supports mobile deployment, it is less optimized for mobile platforms compared to some other specialized frameworks, leading to potential performance drawbacks.

Analysis of Probe.ly

Overall verdict

  • Probely is a solid choice for web vulnerability scanning, particularly appreciated for its automation features and ease of integration into the development lifecycle. It effectively balances accessibility for non-experts with depth of information required by professionals.

Why this product is good

  • Probely is considered effective because it provides automated web vulnerability scanning and is tailored for various user levels, from developers to security experts. It offers continuous scanning and integration capabilities that help streamline the process of identifying and addressing security vulnerabilities. The user-friendly interface and detailed reports facilitate easier understanding and action on the findings.

Recommended for

    Probely is especially recommended for small to medium-sized businesses, development teams, and security professionals who benefit from automated security scanning tools that integrate seamlessly with CI/CD processes. It's also useful for organizations looking to improve their security posture without requiring extensive security expertise.

Probe.ly videos

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TensorFlow videos

What is Tensorflow? - Learn Tensorflow for Machine Learning and Neural Networks

More videos:

  • Tutorial - TensorFlow In 10 Minutes | TensorFlow Tutorial For Beginners | Deep Learning & TensorFlow | Edureka
  • Review - TensorFlow in 5 Minutes (tutorial)

Category Popularity

0-100% (relative to Probe.ly and TensorFlow)
Web Application Security
100 100%
0% 0
Data Science And Machine Learning
Security
100 100%
0% 0
AI
0 0%
100% 100

User comments

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Reviews

These are some of the external sources and on-site user reviews we've used to compare Probe.ly and TensorFlow

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TensorFlow Reviews

7 Best Computer Vision Development Libraries in 2024
From the widespread adoption of OpenCV with its extensive algorithmic support to TensorFlow's role in machine learning-driven applications, these libraries play a vital role in real-world applications such as object detection, facial recognition, and image segmentation.
10 Python Libraries for Computer Vision
TensorFlow and Keras are widely used libraries for machine learning, but they also offer excellent support for computer vision tasks. TensorFlow provides pre-trained models like Inception and ResNet for image classification, while Keras simplifies the process of building, training, and evaluating deep learning models.
Source: clouddevs.com
25 Python Frameworks to Master
Keras is a high-level deep-learning framework capable of running on top of TensorFlow, Theano, and CNTK. It was developed by Franรงois Chollet in 2015 and is designed to provide a simple and user-friendly interface for building and training deep learning models.
Source: kinsta.com
Top 8 Alternatives to OpenCV for Computer Vision and Image Processing
TensorFlow is an open-source software library for dataflow and differentiable programming across a range of tasks such as machine learning, computer vision, and natural language processing. It provides excellent support for deep learning models and is widely used in several industries. TensorFlow offers several pre-trained models for image classification, object detection,...
Source: www.uubyte.com
PyTorch vs TensorFlow in 2022
There are a couple of notable exceptions to this rule, the most notable being that those in Reinforcement Learning should consider using TensorFlow. TensorFlow has a native Agents library for Reinforcement Learning, and Deepmindโ€™s Acme framework is implemented in TensorFlow. OpenAIโ€™s Baselines model repository is also implemented in TensorFlow, although OpenAIโ€™s Gym can be...

Social recommendations and mentions

Based on our record, TensorFlow should be more popular than Probe.ly. It has been mentiond 8 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.

Probe.ly mentions (3)

  • Automated ways to security audit your website
    There are many tools available for this, e.g. Burp Suite, ZAP, etc. We've evaluated a few and found Probely to be the most comprehensive. They have a trial, so your first few scans will be free. After each scan, you will get a report that includes a list of all findings and a recommendation on how to fix them. You will also get a PCI-DSS and OWASP compliance report. - Source: dev.to / almost 2 years ago
  • How to Build Security for your SaaS User Communications
    Our fourth recommendation, if you want to heavily fortify your security controls, is to have a third-party service audit your infrastructure and processes for any vulnerabilities. You can either hire a consultant or use application vulnerability scanners. Examples include Probely or Tenable. If you are looking to gain any compliance certifications, these security audits can offer a headstart by offering you... - Source: dev.to / about 4 years ago
  • Acunetix "target" locks
    Hey mate, give Probely a try :) Just go to https://probely.com/ and Request a Demo. Cheers! Source: over 4 years ago

TensorFlow mentions (8)

  • Why 70% of Americans See AI as a Wealth Inequality Machine: The Developer's Role in Building Fairer Tech
    The open-source movement offers hope here. Projects like Hugging Face are democratizing access to state-of-the-art models, while initiatives like Google's TensorFlow provide powerful frameworks without licensing costs. But even open-source solutions require technical expertise that many lack. - Source: dev.to / 4 months ago
  • Creating Image Frames from Videos for Deep Learning Models
    Converting the images to a tensor: Deep learning models work with tensors, so the images should be converted to tensors. This can be done using the to_tensor function from the PyTorch library or convert_to_tensor from the Tensorflow library. - Source: dev.to / over 3 years ago
  • Need help with a Tensorflow function
    So I went to tensorflow.org to find some function that can generate a CSR representation of a matrix, and I found this function https://www.tensorflow.org/api_docs/python/tf/raw_ops/DenseToCSRSparseMatrix. Source: about 4 years ago
  • Help: Slow performance with windows 10 compared to Ubuntu 20.04 with TF2.7
    Can anyone offer up an explanation for why there is a performance difference, and if possible, what could be done to fix it. I'm using the installation guidelines found on tensorflow.org and installing tf2.7 through pip using an anaconda3 env. Source: about 4 years ago
  • [Question] What are the best tutorials and resources for implementing NLP techniques on TensorFlow?
    I don't have much experience with TensorFlow, but I'd recommend starting with TensorFlow.org. Source: over 4 years ago
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What are some alternatives?

When comparing Probe.ly and TensorFlow, you can also consider the following products

Detectify - Detectify provides a user friendly and thorough web security scan that allows you to focus 100% on web development.

PyTorch - Open source deep learning platform that provides a seamless path from research prototyping to...

Netsparker - Netsparker is a tool for scanning web sites for security vulnerabilities.

Keras - Keras is a minimalist, modular neural networks library, written in Python and capable of running on top of either TensorFlow or Theano.

Intruder - Intruder is a security monitoring platform for internet-facing systems.

IBM Watson Studio - Learn more about Watson Studio. Increase productivity by giving your team a single environment to work with the best of open source and IBM software, to build and deploy an AI solution.