Software Alternatives, Accelerators & Startups
Register | Login

TensorFlow VS Keywords Everywhere

Compare TensorFlow VS Keywords Everywhere and see what are their differences

Electe
Discover Electe, our data analytics platform dedicated to SMEs. Don't let your data go unused, take your business into the future! featured
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.
Contents:
  1. » Base Details
  2. » Videos
  3. » Reviews
  4. » Alternatives

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.

Keywords Everywhere logo Keywords Everywhere

Free browser add-on for keyword volume, CPC & competition
  • TensorFlow Landing page
    Landing page //
    2023-06-19
  • Keywords Everywhere Landing page
    Landing page //
    2023-09-19

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.

Keywords Everywhere features and specs

  • Comprehensive Metrics
    Keywords Everywhere provides detailed metrics such as search volume, CPC, and competition data, helping users make informed decisions for SEO and PPC strategies.
  • Ease of Use
    The browser extension integrates seamlessly with essential tools like Google Search, YouTube, and Google Analytics, making it convenient to access keyword data directly from these platforms.
  • Affordability
    Offers a pay-as-you-go pricing model, which can be more cost-effective for small businesses and individual users compared to subscription-based services.
  • Data Across Platforms
    Provides keyword data for multiple platforms including Google, YouTube, Amazon, and more, which is valuable for diverse digital marketing strategies.
  • Time Saver
    By displaying keyword metrics directly in search engine results and other tools, it significantly reduces the time needed to gather and analyze keyword data.

Possible disadvantages of Keywords Everywhere

  • Limited Free Version
    The free version offers very limited features, driving users to purchase credits for more comprehensive data.
  • Dependency on Browser Extension
    Requires a browser extension to function, which may not be suitable for all users or devices and could raise privacy/security concerns.
  • Accuracy Variability
    As with many keyword tools, the accuracy of the data can occasionally be inconsistent, which may affect strategic decisions.
  • Limited Advanced Features
    While great for basic keyword research, it lacks some of the advanced features offered by more robust SEO tools, such as detailed competitive analysis or site audits.
  • Potential for Data Overload
    The abundance of data displayed can sometimes be overwhelming, particularly for beginners who may struggle to interpret and utilize it effectively.

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)

Keywords Everywhere videos

+ Add

How to use Keywords Everywhere - SEO keyword research tool

More videos:

  • Review - KEYWORDS EVERYWHERE is now a PAID TOOL - Here's What To Do - Keywords Everywhere Alternative
  • Tutorial - Keywords Everywhere | A Tutorial + Advice on Keywords for YouTube
  • Review - Keywords Everywhere Review: Better Alternative to Google Keyword Planner
  • Review - Keywords Everywhere Review | Best Keyword Search Volume Chrome Extension! 🚀
  • Review - Keywords Everywhere Review 2021 | Keyword research Tool

Category Popularity

0-100% (relative to TensorFlow and Keywords Everywhere)

TensorFlow

Keywords Everywhere

Data Science And Machine Learning
100 100%
Data Science And Machine Learning
0% 0
SEO Tools
0 0%
SEO Tools
100% 100
AI
84 84%
AI
16% 16
SEO
0 0%
SEO
100% 100

User comments

Share your experience with using TensorFlow and Keywords Everywhere. For example, how are they different and which one is better?
Log in or Post with

Reviews

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

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

Keywords Everywhere Reviews

112 Best Chrome Extensions You Should Try (2021 List)
Keywords Everywhere is an alternative to Ubersuggest, a freemium keyword research tool. It shows the search query data on more than 15 websites. For free users, it shows a trend chart, long-tail keywords, and keywords from ‘people also search for’. But, paid users can see monthly search volume, CPC, competition, and trend data. Although solely for keyword research, you do...
Source: www.einsstark.tech
9 Free Keyword Research Tools (That CRUSH Google Keyword Planner)
Keywords Everywhere is a free add-on for Chrome (or Firefox). It adds search volume, CPC & competition data to all your favourite websites.
Source: ahrefs.com
73 Best SEO tools 2021 – The Most Epic List You Shouldn’t Miss
While most use this tool strictly for Paid ads, Keywords Everywhere is very useful to help you discover long-tail keywords related to the ones you are searching for on Google.
Source: blog.linkody.com

Social recommendations and mentions

Based on our record, Keywords Everywhere should be more popular than TensorFlow. It has been mentiond 16 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

Keywords Everywhere mentions (16)

  • SEO 101 for Software Developers
    To find keywords I use the tool Keywords Everywhere. It gives you information on how many people search for a particular keyword a month, how difficult it will be to rank for, as well ideas for additional keywords. - Source: dev.to / over 1 year ago
  • How to Manage Your Time as a Software Developer ⌛️
    For example, I do a lot of keyword research for my blog posts and YouTube videos. This generally consists of searching for keywords on Google and then copying the numbers that I get from Keywords Everywhere into a spreadsheet. - Source: dev.to / about 2 years ago
  • My Guide To Shopify Store Keyword Research
    You may be thinking to yourself well that's it right? I know what works and what doesn't, well not exactly because you don't just want to copy everything your competition does or you'll be competing with them all the time and that's a losing battle for most small stores. So step 2 is I cross reference it with another tool called keywords everywhere. As I mentioned this tool can be similar to Ahrefs as you can scan... Source: about 2 years ago
  • GMB Stats?
    Keywords everywhere again, not sure if it's match for you. Source: about 2 years ago
  • Keyword research
    Step 2: keywordseverywhere.com ($10 for 100K SV check - it's a chrome extension), run your list through this and get all SV. Source: about 2 years ago
View more

What are some alternatives?

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

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

KeywordTool.io - KeywordTool.io is the best FREE alternative to Google Keyword Planner and Ubersuggest. It uses Google's autocomplete feature to get over 750+ long-tail keywords for any given query.

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

Moz - Backed by industry-leading data and the largest community of SEOs on the planet, Moz builds tools that make inbound marketing easy.

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

Ahrefs - Ahrefs is a toolset for SEO and marketing. We have tools for backlink research, organic traffic research, keyword research, content marketing & more. Give Ahrefs a try!

Loading...