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Bright Data VS TensorFlow

Compare Bright Data VS TensorFlow and see what are their differences

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Clear, Fast & Unlimited. Residential & Mobile Proxies For Best Price. featured
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  3. » Reviews
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Bright Data logo Bright Data

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

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.
  • Bright Data Landing page
    Landing page //
    2021-05-12
  • TensorFlow Landing page
    Landing page //
    2023-06-19

Bright Data features and specs

  • Extensive Proxy Network
    Bright Data offers a vast and diverse network of over 72 million IPs, ensuring high availability and reliability for users.
  • Wide Range of Services
    Provides various proxy solutions including data center, residential, mobile, and ISP proxies, catering to different user needs.
  • Geographical Targeting
    Allows users to target proxies based on specific countries, cities, and even ASN, which is beneficial for localized data scraping.
  • Advanced Tools and APIs
    Offers sophisticated tools and APIs for automation, data extraction, and optimized proxy management.
  • Customer Support
    Provides round-the-clock customer support and numerous resources such as detailed documentation and integration guides.

Possible disadvantages of Bright Data

  • Cost
    Bright Data's services are priced at a premium, which might be expensive for small businesses or individual users.
  • Complexity
    The extensive range of options and settings can be overwhelming and may require a steep learning curve for new users.
  • Ethical Concerns
    The use of residential and mobile proxies can raise ethical questions regarding user consent and data privacy.
  • Account Approval
    New accounts are subject to approval which can delay immediate access to the service.
  • Occasional IP Blocks
    Despite the large IP pool, users may still experience occasional blocks and captchas when accessing certain websites.

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.

Bright Data videos

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Rotating Residential Network | Proxy Network Types | Bright Data (Formerly Luminati Networks)

TensorFlow videos

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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 Bright Data and TensorFlow)

Bright Data

TensorFlow

Proxy
100 100%
Proxy
0% 0
Data Science And Machine Learning
0 0%
Data Science And Machine Learning
100% 100
Residential Proxies
100 100%
Residential Proxies
0% 0
AI
0 0%
AI
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 Bright Data and TensorFlow

Bright Data Reviews

  1. Sam Mitchell
    · Owner at KittenProperties ·
    Mixed feelings

    We used their DC proxies and Residential proxies. Resi proxies were having quite low success rate. We had to use resi solution from other proxy providers. Unblocker didn't work well either also it was way too expensive.

    🏁 Competitors: Smartproxy, NetNut.io
    👍 Pros:    Cheap dc proxies
    👎 Cons:    Quite expensive|Residential proxies are worse than competitiors
Top 10 Alternatives to Bright Data (formerly Luminati Proxy Networks)
Oxylabs remains the number aggressive competitor of Bright Data – they have even had a case to settle in the court in the past. If you wouldn’t want to use Bright Data proxies, then you might as well avoid Oxylabsas it is everything you hate in Bright Data and even worse. Aside from the pricing aspect, Oxylabs have been found to engage in some unethical practices and scam...
Source: www.bestproxyreviews.com
911.re Alternatives: 10 Best Proxies Smilar to 911 Proxy in 2023
The most exciting thing about Bright Data is that it comes with new daily feature releases so that you always have access to the latest features as soon as they are released. You also have access to 24/7 global support and dedicated account managers who will help you get started with Bright Data immediately!
Source: www.techuseful.com
17 BEST Residential Proxies to Buy in 2022 (Cheap & Premium)
Formerly known as Luminati Networks, Bright Data is the most popular premium residential proxy provider in the industry.
Source: earthweb.com
10 Best Free Online Proxy Server List of 2022 [VERIFIED]
Verdict: Bright Data Proxy Manager will help you with various use cases such as web data extraction, e-commerce, collecting stock market data, brand protection, etc. Bright Data has capabilities of data collection from eCommerce, Social Media, etc. It provides 24×7 global support and dedicated account managers.
Source: www.softwaretestinghelp.com
How to choose the right proxy service for your bots and scraping (Residential vs. Backconnect vs. Datacenter, and Exclusive vs. Shared proxies)
To be specific, Luminati is literally an order of magnitude ahead of it’s next largest competitor and the pricing of all legally-compliant residential proxy networks (of which there are between 1 and 4, depending on your definition) is, unfortunately, nearly identical. If $500 per month seems like a lot to you, feel free to shop around. Nothing compares and nothing in the...
Source: bulletproofdev.github.io

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.
Source: www.labellerr.com
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...
Source: www.assemblyai.com

Social recommendations and mentions

Based on our record, Bright Data should be more popular than TensorFlow. It has been mentiond 34 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.

Bright Data mentions (34)

  • Reddit Recap: Audio summaries of subreddits powered by BrightData
    Reddit Recap is an application that scrapes subreddits using BrightData and generates concise summaries every two hours. These summaries are then converted into audio briefings, all accessible through a beautiful web app, allowing users to effortlessly stay informed about their favorite communities. - Source: dev.to / 4 months ago
  • State of the Art Automated Web Scraper using Bright Data
    Make sure to sign up on BrightData. Also complete the steps for the initial setup for Proxies & Scraping Infrastructure and Web Scraping API. Please make a note on the WSS Browser Credential, Webscraper Api Token. - Source: dev.to / 5 months ago
  • Make Cursor Composer Smarter with Bright Web Scraping Capabilities
    So my goal here is creating a web scraper and web searcher using bright and gemini openai compatible model to make cursor composer more smarter with functionality like web search and web scrape. - Source: dev.to / 5 months ago
  • How to Use Proxies in Python
    Paid proxies: services like Bright Data or ScraperAPI provide reliable proxies with better performance and support, but you have to pay. - Source: dev.to / 6 months ago
  • Stealth Mode—Enhanced Bot Detection Evasion—Launch week day 3
    (Optional) Using a proxy server. You would need to secure proxy services from an external proxy provider (NetNut, BrightData, or similar) to configure things like host, username, and password separately. - Source: dev.to / 6 months ago
View more

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: almost 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
View more

What are some alternatives?

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

Oxylabs - A web intelligence collection platform and premium proxy provider, enabling companies of all sizes to utilize the power of big data.

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

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.

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

NetNut.io - Residential proxy network with 52M+ IPs worldwide. SERP API, Website Unblocker, Professional Datasets.

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

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