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Zyte VS TensorFlow

Compare Zyte VS TensorFlow and see what are their differences

Note: These products don't have any matching categories. If you think this is a mistake, please edit the details of one of the products and suggest appropriate categories.

Zyte logo Zyte

We're Zyte (formerly Scrapinghub), the central point of entry for all your web data needs.

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.
  • Zyte Landing page
    Landing page //
    2022-01-09

We are the leader in web data extraction technology and services. We're obsessed with data. And what it can do for businesses.

We help thousands of companies and millions of developers to get their hands on clean, accurate data. Quickly, reliably & at scale. Every day, for more than a decade.

From price intelligence, news and media, job listings and entertainment trends, brand monitoring, and more, our customers rely on us to obtain dependable data from over 13 billion web pages each month.

Zyte (formerly Scrapinghub) serves over 2,000 companies and 1 million developers from across the globe who value accurate, reliable web data to help them run their business.

  • TensorFlow Landing page
    Landing page //
    2023-06-19

Zyte features and specs

  • High-Quality Data Extraction
    Zyte provides powerful web scraping capabilities, allowing for reliable and high-quality data extraction from various websites.
  • Ease of Use
    The platform offers a user-friendly interface and comprehensive documentation, making it easier for both beginners and experienced users to navigate and utilize its features.
  • Compliance and Ethical Scraping
    Zyte emphasizes ethical scraping practices and compliance with website terms of service, helping users avoid legal and ethical issues.
  • Custom Solutions
    Zyte offers tailored data extraction solutions to meet specific business needs, providing customization and flexibility.
  • Scalability
    The platform supports scalable data extraction operations, suitable for both small projects and large-scale enterprise needs.

Possible disadvantages of Zyte

  • Cost
    The pricing for Zyte's services can be relatively high, which may be a barrier for small businesses or individual users with limited budgets.
  • Learning Curve
    Despite its user-friendly design, mastering all the advanced features of Zyte may require a learning curve, particularly for users new to web scraping.
  • Rate Limiting
    Some users may encounter rate limiting or blocking from target websites, which can hinder the data extraction process and require additional strategies to manage.
  • Dependency on Third-Party Websites
    As with any web scraping tool, Zyte's effectiveness can be impacted by changes in the HTML structure of target websites or their policies, requiring constant adaptation.
  • Ethical and Legal Restrictions
    While Zyte promotes ethical scraping, users must still navigate complex legal landscapes, which can vary by region and website, adding operational challenges.

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 Zyte

Overall verdict

  • Zyte is considered a good choice for businesses and individuals looking for reliable and efficient web scraping solutions. Its strong customer support, extensive documentation, and user-friendly platform make it well-regarded in the industry.

Why this product is good

  • Zyte (formerly Scrapinghub) is regarded as a good platform because it provides a comprehensive set of tools and services for web data extraction and web scraping. It offers easy-to-use APIs, a robust infrastructure for large-scale data scraping, and services like automated data retrieval and storage. Additionally, Zyte is recognized for its ability to handle complex scraping tasks, such as data extraction from dynamic websites using AJAX or JavaScript.

Recommended for

  • Data scientists and analysts needing web data for research and insights
  • Developers seeking APIs for efficient and scalable data extraction
  • Business professionals requiring market and competitor insights
  • Companies looking for automated and reliable data extraction services

Zyte videos

What is data exraction?

More videos:

  • Review - Scraping and sentiment analysis using Scrapinghub and Amazon Comrehend

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 Zyte and TensorFlow)
Web Scraping
100 100%
0% 0
Data Science And Machine Learning
Data Extraction
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 Zyte and TensorFlow

Zyte Reviews

Creating an Automated Text Extraction Workflow — Part 1
The 600 lbs gorilla, Diffbot, comes with a swath of solid APIs but starts at $300, which is ridiculous if you’re just extracting text. Scrapinghub’s News API, Extractor API, and plenty more are better priced if you want an affordable alternative; plus, Extractor API includes a visual online tool for extracting hundreds of articles at once, if you want to do things via UI.
Source: medium.com

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 François 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 Deepmind’s Acme framework is implemented in TensorFlow. OpenAI’s Baselines model repository is also implemented in TensorFlow, although OpenAI’s Gym can be...

Social recommendations and mentions

Based on our record, TensorFlow should be more popular than Zyte. It has been mentiond 7 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.

Zyte mentions (1)

TensorFlow mentions (7)

  • 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 2 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: almost 3 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 3 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: about 3 years ago
  • [Question] What are the best tutorials and resources for implementing NLP techniques on TensorFlow?
    I have looked at this TensorFlow website and TensorFlow.org and some of the examples are written by others, and it seems that I am stuck in RNNs. What is the best way to install TensorFlow, to follow the documentation and learn the methods in RNNs in Python? Is there a good tutorial/resource? Source: about 3 years ago
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What are some alternatives?

When comparing Zyte and TensorFlow, you can also consider the following products

Bright Data - World's largest proxy service with a residential proxy network of 72M IPs worldwide and proxy management interface for zero coding.

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

Apify - Apify is a web scraping and automation platform that can turn any website into an API.

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

Smartproxy - Smartproxy is perhaps the most user-friendly way to access local data anywhere. It has global coverage with 195 locations, offers more than 55M residential proxies worldwide and a great deal of scraping solutions.

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