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Distill.io VS PyTorch

Compare Distill.io VS PyTorch and see what are their differences

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Distill.io logo Distill.io

Distill.io is one of the advanced page monitoring tools used by professionals to monitor dynamic pages, feeds, and iframes.

PyTorch logo PyTorch

Open source deep learning platform that provides a seamless path from research prototyping to...
  • Distill.io Landing page
    Landing page //
    2023-07-27
  • PyTorch Landing page
    Landing page //
    2023-07-15

Distill.io features and specs

  • Real-time Monitoring
    Distill.io provides real-time monitoring capabilities, allowing users to track changes on websites as they happen. This is particularly useful for keeping up-to-date with time-sensitive information.
  • Customization
    Users can customize the tracking frequency and specific elements to monitor on a webpage, giving them control over what information they want to track and how often they receive updates.
  • User-friendly Interface
    The platform offers a straightforward and intuitive interface, making it accessible for users without extensive technical skills to set up website monitoring.
  • Multi-platform Support
    Distill.io supports various platforms including web browsers, mobile devices, and desktops, providing users with flexibility in accessing their monitoring data.

Possible disadvantages of Distill.io

  • Limited Free Plan
    The free version of Distill.io has significant restrictions on the number of monitors and frequency of checks, which may not be sufficient for users with extensive monitoring needs.
  • Potentially High Costs
    For users requiring more frequent monitoring or additional features, the cost can escalate, making it less affordable for personal or small business use.
  • Complex Setup for Advanced Users
    While the basic setup is user-friendly, configuring more advanced monitoring options can be complex and challenging for those who are not technically inclined.
  • Browser Dependency
    Distill.io is heavily reliant on web browsers, which could lead to issues if there are changes or updates to browser security settings or compatibility.

PyTorch features and specs

  • Dynamic Computation Graph
    PyTorch uses a dynamic computation graph, which allows for interactive and flexible model building. This is particularly beneficial for researchers who need to modify the network architecture on-the-fly.
  • Pythonic Nature
    PyTorch is designed to be deeply integrated with Python, making it very intuitive for Python developers. The framework feels more 'native' to Python, which improves the ease of learning and use.
  • Strong Community Support
    PyTorch has a large, active, and growing community. This means abundant resources such as tutorials, forums, and third-party tools are available to help developers solve problems and share solutions.
  • Flexibility and Control
    PyTorch offers granular control over computations and provides extensive debugging capabilities. This level of control is beneficial for tasks that require precise tuning and custom implementations.
  • Support for GPU Acceleration
    PyTorch offers seamless integration with GPU hardware, which significantly accelerates the computation process. This makes it highly efficient for deep learning tasks.
  • Rich Ecosystem
    PyTorch has a rich ecosystem including libraries like torchvision, torchaudio, and torchtext, which are specialized for different data types and can significantly shorten development times.

Possible disadvantages of PyTorch

  • Limited Production Deployment Tools
    PyTorch is primarily designed for research rather than production. While deployment tools like TorchServe exist, they are not as mature or integrated as solutions offered by other frameworks like TensorFlow.
  • Lesser Adoption in Industry
    While PyTorch is popular among researchers, it has historically seen less adoption in industry compared to TensorFlow, which means there might be fewer resources for large-scale production deployments.
  • Inconsistent API Changes
    As PyTorch continues to evolve rapidly, occasionally there are breaking changes or inconsistent API updates. This can create maintenance challenges for existing codebases.
  • Steeper Learning Curve for Beginners
    Despite its Pythonic design, PyTorch's focus on flexibility and control can make it slightly harder for beginners to get started compared to some other high-level libraries and frameworks.
  • Less Mature Documentation
    Although the documentation is improving, it has been historically less comprehensive and mature compared to other frameworks like TensorFlow, which can make it difficult to find detailed, clear information.

Analysis of PyTorch

Overall verdict

  • Yes, PyTorch is considered a good deep learning framework.

Why this product is good

  • Ease of Use: PyTorch has an intuitive interface that makes it easier to learn and use, especially for beginners.
  • Dynamic Computation Graphs: PyTorch employs dynamic computation graphs, which provide more flexibility in building and modifying models on the fly.
  • Strong Community and Support: PyTorch has a large and active community, offering extensive resources, forums, and tutorials.
  • Research Adoption: PyTorch is widely adopted in the research community, making state-of-the-art models and techniques readily available.
  • Integration: PyTorch integrates well with other libraries and tools in the Python ecosystem, providing robust support for various applications.

Recommended for

  • Researchers and Academics: Ideal for those who need a flexible and dynamic tool for experimenting with new models and techniques.
  • Industry Practitioners: Suitable for developers and data scientists working on production-level machine learning solutions.
  • Educators and Learners: Great for educational purposes due to its easy-to-understand syntax and comprehensive documentation.

Distill.io videos

+ Add

How To Monitor Website Changes? - Distill.io Chrome Extension

More videos:

  • Review - Data Alerts with Distill.io

PyTorch videos

+ Add

PyTorch in 5 Minutes

More videos:

  • Review - Jeremy Howard: Deep Learning Frameworks - TensorFlow, PyTorch, fast.ai | AI Podcast Clips
  • Review - PyTorch at Tesla - Andrej Karpathy, Tesla

Category Popularity

0-100% (relative to Distill.io and PyTorch)

Distill.io

PyTorch

Monitoring Tools
100 100%
Monitoring Tools
0% 0
Data Science And Machine Learning
0 0%
Data Science And Machine Learning
100% 100
Website Monitoring
100 100%
Website Monitoring
0% 0
Data Science Tools
0 0%
Data Science Tools
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 Distill.io and PyTorch

Distill.io Reviews

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PyTorch Reviews

10 Python Libraries for Computer Vision
Similar to TensorFlow and Keras, PyTorch and torchvision offer powerful tools for computer vision tasks. PyTorch’s dynamic computation graph and torchvision’s datasets and pre-trained models make it easy to implement tasks such as image classification, object detection, and style transfer.
Source: clouddevs.com
25 Python Frameworks to Master
Along with TensorFlow, PyTorch (developed by Facebook’s AI research group) is one of the most used tools for building deep learning models. It can be used for a variety of tasks such as computer vision, natural language processing, and generative models.
Source: kinsta.com
Top 8 Alternatives to OpenCV for Computer Vision and Image Processing
PyTorch is another open-source machine learning framework that is widely used in academia and industry. PyTorch provides excellent support for building deep learning models, and it has several pre-trained models for computer vision tasks, making it the ideal tool for several computer vision applications. PyTorch offers a user-friendly interface that makes it easier for...
Source: www.uubyte.com
PyTorch vs TensorFlow in 2022
When we compare HuggingFace model availability for PyTorch vs TensorFlow, the results are staggering. Below we see a chart of the total number of models available on HuggingFace that are either PyTorch or TensorFlow exclusive, or available for both frameworks. As we can see, the number of models available for use exclusively in PyTorch absolutely blows the competition out of...
Source: www.assemblyai.com
15 data science tools to consider using in 2021
First released publicly in 2017, PyTorch uses arraylike tensors to encode model inputs, outputs and parameters. Its tensors are similar to the multidimensional arrays supported by NumPy, another Python library for scientific computing, but PyTorch adds built-in support for running models on GPUs. NumPy arrays can be converted into tensors for processing in PyTorch, and vice...
Source: searchbusinessanalytics.techtarget.com

Social recommendations and mentions

Based on our record, PyTorch should be more popular than Distill.io. It has been mentiond 133 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.

Distill.io mentions (82)

  • Tips for people waiting for the Refurbished Steam Deck restock
    First of all, you probably don't want to manually refresh the Steam page to check if the SD is back in stock, so I recommend installing a website monitoring extension. There are a few out there but I can vouch for distill.io because it has a free tier with unlimited local checks. Set the intervals as low as you want, but keep in mind that the last restock lasted about 45 minutes - 1 hour. I personally set mine to... Source: almost 2 years ago
  • Website change trackers
    Recently found out about website change trackers and had to share, like distill.io and fetchnotifs (not affiliated btw). I use them like everyday for amazon items and general stuff. Source: almost 2 years ago
  • Canyon Endurace CF out of stock
    You can also try notify-me.rs . It's super simple tracker, and has more checks than distill.io , we have bunch of people from this subreddit using it already! Source: almost 2 years ago
  • NEW SERIES OF JEFF DRAWINGS ON SALE
    Were these even advertised anywhere online? Insane how fast the 6x8s went. Glad I've had a distill.io alert set there for like 2 years now haha. Source: almost 2 years ago
  • What is the best free tool or code to monitor visual changes to a website in real time? (e.g. Distill.io)
    Distill.io offers every 5 seconds but it seems I need an upgraded account to be able to select this interval using the Device "Cloud-Distill's Severs (this device)". So it seems I'd need to always be on my computer in order for it to run. So I selected "Any Local Device (beta)" for device. Description for "Device" = Select device that this monitor runs on. Other devices will appear in the list once all devices... Source: almost 2 years ago
View more

PyTorch mentions (133)

  • Grasping Computer Vision Fundamentals Using Python
    To aspiring innovators: Dive into open-source frameworks like OpenCV or PyTorch, experiment with custom object detection models, or contribute to projects tackling bias mitigation in training datasets. Computer vision isn’t just a tool, it’s a bridge between the physical and digital worlds, inviting collaborative solutions to global challenges. The next frontier? Systems that don’t just interpret visuals, but... - Source: dev.to / about 1 month ago
  • Top Programming Languages for AI Development in 2025
    With the quick emergence of new frameworks, libraries, and tools, the area of artificial intelligence is always changing. Programming language selection. We're not only discussing current trends; we're also anticipating what AI will require in 2025 and beyond. - Source: dev.to / about 1 month ago
  • Fine-tuning LLMs locally: A step-by-step guide
    Next, we define a training loop that uses our prepared data and optimizes the weights of the model. Here's an example using PyTorch:. - Source: dev.to / 2 months ago
  • 10 Must-Have AI Tools to Supercharge Your Software Development
    8. TensorFlow and PyTorch: These frameworks support AI and machine learning integrations, allowing developers to build and deploy intelligent models and workflows. TensorFlow is widely used for deep learning applications, offering pre-trained models and extensive documentation. PyTorch provides flexibility and ease of use, making it ideal for research and experimentation. Both frameworks support neural network... - Source: dev.to / 4 months ago
  • Automating Enhanced Due Diligence in Regulated Applications
    Frameworks like TensorFlow and PyTorch can help you build and train models for various tasks, such as risk scoring, anomaly detection, and pattern recognition. - Source: dev.to / 4 months ago
View more

What are some alternatives?

When comparing Distill.io and PyTorch, you can also consider the following products

Visualping - Visualping is the easiest to use website checker, webpage change monitoring, website change detector and website change alert software of the web. Read more about Visualping.

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.

Monity.ai - Monitor website changes in real time with Monity.ai – Stay informed with AI-powered alerts and never miss anything happening on the internet.

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

Browse AI - Automate any workflow on any website with no code. Used for monitoring, testing, automation, and data aggregation.Sign up now for free and receive 2x jobs per month – forever!

Scikit-learn - scikit-learn (formerly scikits.learn) is an open source machine learning library for the Python programming language.

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