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TensorFlow VS Apify

Compare TensorFlow VS Apify and see what are their differences

Piloterr
Piloterr web scraping API handles headless browsers, rotates proxies for you, and offers a library featured
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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.

Apify logo Apify

Apify is a web scraping and automation platform that can turn any website into an API.
  • TensorFlow Landing page
    Landing page //
    2023-06-19
  • Apify Landing page
    Landing page //
    2023-09-30

Apify is a JavaScript & Node.js based data extraction tool for websites that crawls lists of URLs and automates workflows on the web. With Apify you can manage and automatically scale a pool of headless Chrome / Puppeteer instances, maintain queues of URLs to crawl, store crawling results locally or in the cloud, rotate proxies and much more.

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.

Apify features and specs

  • Ease of Use
    Apify provides a user-friendly interface that makes it easy for users of all technical levels to create and manage web scraping tasks.
  • Scalability
    Apify is built to handle tasks of various sizes, from small-scale projects to enterprise-level operations, making it a scalable solution.
  • Integration and API Support
    It offers extensive API support, allowing for seamless integration with other tools and systems to enhance automated workflows.
  • Customizability
    Users can customize their scraping bots (actors) with different settings and scripts to fit specific needs and requirements.
  • Cloud-based
    Being a cloud-based platform, Apify allows users to run their scraping tasks without needing local resources, which is convenient and efficient.
  • Comprehensive Documentation
    Apify provides thorough documentation and tutorials, which help users get started quickly and solve issues efficiently.
  • Community and Support
    Apify has an active community and solid customer support to assist users with their needs and enhance their overall experience.

Possible disadvantages of Apify

  • Learning Curve
    While the interface is user-friendly, there may still be a learning curve for those new to web scraping and automation.
  • Cost
    Apify can be expensive compared to other web scraping tools, particularly for extensive use cases that require high volumes of data.
  • Dependency on External Factors
    Web scraping often depends on the stability of the target websites. Changes in website structures can break scripts, requiring ongoing maintenance.
  • Performance Limitations
    The performance of cloud-based scraping tasks can be affected by network latency and other external factors beyond user control.
  • Potential Legal Issues
    Web scraping can raise legal concerns, particularly when scraping data from websites that restrict such activities in their terms of service.
  • Resource Intensity
    Complex scraping tasks can be resource-intensive, potentially requiring higher-tier subscriptions and more computing resources, driving up costs.

Analysis of Apify

Overall verdict

  • Yes, Apify is considered a good choice for web scraping and automation needs due to its comprehensive features, user-friendly interface, and strong community support. It is especially beneficial for those who require efficient, large-scale data extraction and workflow automation.

Why this product is good

  • Apify is an established platform known for its robust web scraping and automation capabilities. It provides a powerful API, pre-built actors for common tasks, and allows you to create custom web scrapers with ease. The platform is scalable, supports a variety of programming languages, and offers features like scheduling, proxies, and data storage solutions. This versatility makes it a valuable tool for businesses and developers needing efficient data retrieval and workflow automation.

Recommended for

  • Developers looking for a versatile web scraping solution.
  • Businesses needing to automate data collection processes.
  • Researchers and analysts requiring extensive data from the web.
  • Marketers seeking competitive analysis through data scraping.
  • Tech enthusiasts interested in exploring web automation tools.

TensorFlow videos

+ Add

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)

Apify videos

+ Add

Apify product news - 2019/01/30

Category Popularity

0-100% (relative to TensorFlow and Apify)

TensorFlow

Apify

Data Science And Machine Learning
100 100%
Data Science And Machine Learning
0% 0
Web Scraping
0 0%
Web Scraping
100% 100
AI
100 100%
AI
0% 0
Data Extraction
0 0%
Data Extraction
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 TensorFlow and Apify

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

Apify Reviews

Top 15 Best TinyTask Alternatives in 2022
This is another tinytask alternative. For you to link various web services and APIs, Apify has provided many web integration options. You can add data processing and customised computation processes in addition to letting the data flow between them. With the data that is freely accessible on the web, you may provide crucial insights, and easy lead creation allows you to...
Source: www.dashtech.org

Social recommendations and mentions

Based on our record, Apify should be more popular than TensorFlow. It has been mentiond 26 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.

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
View more

Apify mentions (26)

  • How to scrape TikTok using Python
    For deployment, we'll use the Apify platform. It's a simple and effective environment for cloud deployment, allowing efficient interaction with your crawler. Call it via API, schedule tasks, integrate with various services, and much more. - Source: dev.to / about 1 month ago
  • How to scrape Bluesky with Python
    We already have a fully functional implementation for local execution. Let us explore how to adapt it for running on the Apify Platform and transform in Apify Actor. - Source: dev.to / 3 months ago
  • Web scraping with GPT-4o: powerful but expensive
    We've had the best success by first converting the HTML to a simpler format (i.e. markdown) before passing it to the LLM. There are a few ways to do this that we've tried, namely Extractus[0] and dom-to-semantic-markdown[1]. Internally we use Apify[2] and Firecrawl[3] for Magic Loops[4] that run in the cloud, both of which have options for simplifying pages built-in, but for our Chrome Extension we use... - Source: Hacker News / 9 months ago
  • Current problems and mistakes of web scraping in Python and tricks to solve them!
    Developed by Apify, it is a Python adaptation of their famous JS framework crawlee, first released on Jul 9, 2019. - Source: dev.to / 10 months ago
  • Show HN: Crawlee for Python – a web scraping and browser automation library
    Hey all, This is Jan, the founder of [Apify](https://apify.com/)—a full-stack web scraping platform. After the success of [Crawlee for JavaScript](https://github.com/apify/crawlee/) today! The main features are: - A unified programming interface for both HTTP (HTTPX with BeautifulSoup) & headless browser crawling (Playwright). - Source: Hacker News / 11 months ago
View more

What are some alternatives?

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

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

import.io - Import. io helps its users find the internet data they need, organize and store it, and transform it into a format that provides them with the context they need.

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

Scrapy - Scrapy | A Fast and Powerful Scraping and Web Crawling Framework

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

Octoparse - Octoparse provides easy web scraping for anyone. Our advanced web crawler, allows users to turn web pages into structured spreadsheets within clicks.

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