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Adalo VS TensorFlow

Compare Adalo VS TensorFlow and see what are their differences

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Build powerful web apps, and create your custom AI apps, no code needed! featured
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  3. » Reviews
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Adalo logo Adalo

Build apps for every platform, without code ✨

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.
  • Adalo Landing page
    Landing page //
    2023-09-26
  • TensorFlow Landing page
    Landing page //
    2023-06-19

Adalo features and specs

  • User-Friendly Interface
    Adalo offers a highly intuitive drag-and-drop interface, making it accessible for users without technical skills.
  • Rapid Prototyping
    The platform allows for quick design and deployment, enabling users to rapidly prototype and test their applications.
  • Integration with Various Services
    Adalo supports integration with a variety of third-party services and APIs, enhancing its functionality and versatility.
  • Customizable Components
    Users can customize pre-built components or create their own, offering flexibility in app design.
  • Cross-Platform Capability
    Adalo enables the development of apps for both iOS and Android platforms, as well as web applications.

Possible disadvantages of Adalo

  • Performance Issues
    Some users report slower loading times and performance issues, especially with complex applications.
  • Limited Scalability
    The platform may not be suitable for highly scalable applications or those requiring advanced functionality.
  • Subscription Costs
    While Adalo offers a free tier, the more useful features are behind a paywall, which can become costly for continued use.
  • Data Storage Constraints
    Users are often limited by the amount of data they can store, which could be a downside for data-intensive applications.
  • Dependency on No-Code Environment
    Relying heavily on a no-code solution can limit technical growth and may not be suitable if custom coding becomes necessary.

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.

Adalo videos

+ Add

No Code Summit at Microsoft NYC: Adalo

More videos:

  • Review - Introducing Adalo | Create Your Own App Without Code
  • Tutorial - Adalo Tutorial

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)

Category Popularity

0-100% (relative to Adalo and TensorFlow)

Adalo

TensorFlow

Application Builder
100 100%
Application Builder
0% 0
Data Science And Machine Learning
0 0%
Data Science And Machine Learning
100% 100
No Code
100 100%
No Code
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 Adalo and TensorFlow

Adalo Reviews

THE BEST 34 APP DEVELOPMENT SOFTWARE IN 2022 LIST
You can bring your app ideas to life with Adalo. Creating web and mobile apps today requires learning how to code, finding a technical cofounder, or raising a lot of capital. For some, this means spending lots of precious time and money before they can get their idea off the ground. For others, this cost is simply too high and they walk away from their dream. With Adalo app...
Source: www.edigitalagency.com.au
21 Best No Code Tools You Need To Try
Whilst it may seem similar to Glide above, Adalo is focused more on the visual “drag-and-drop” user experience so users can instantly see what they build in real-time.
Source: www.cenario.co
33+ Best No Code Tools you will love 😍
Building No Code Apps has never been easier with Adalo as a platform of choice. You can build functional, advanced apps with Adalo which honestly can replicate custom code apps you may pay thousands for with a developer.
Source: www.dansiepen.io
25 No-Code Apps and Tools to help build your next Startup
Adalo is an amazing and intuitive way to build beautiful applications! Adalo-built apps can work on both the Apple App Store and the Google Play Store. Adalo’s top selling point is the easy to use “drag and drop” feature which allows you to watch the progress and design of your app in real time. The huge community of makers happily share their tips and tricks to great...
Source: www.ishir.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.
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, TensorFlow should be more popular than Adalo. 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.

Adalo mentions (3)

  • Ask HN: Repair and Maintenance App
    Yes, I think no-code solution can work easily for this use case. There are no of solutions you can try and see which one fits best in your use case. https://bubble.io, https://drapcode.com, etc works best for web apps. If you need Mobile Apps, then you can try using https://adalo.com or Thunkable/GlideApps etc. - Source: Hacker News / almost 4 years ago
  • Retool alternative which not charge per user?
    Thanks, but it look so expensive. For mobile app, I still evaluating thunkable.com and adalo.com. Source: almost 4 years ago
  • Amazon Honeycode is here to shake up the no code market
    After dropping several hints in recent months, AWS finally launched the beta version of Amazon Honeycode, the company’s spanking new rendition of a no-code product. For the longest time, customers of the no-code market segment have turned to brands like bubble.io and adalo.com for quick and engaging app development projects. But with Beta Honeycode now around, it’s interesting to see what tricks AWS has up its... Source: almost 4 years ago

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
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What are some alternatives?

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

Bubble.io - Building tech is slow and expensive. Bubble is the most powerful no-code platform for creating digital products.

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

zeroqode - Build your app up to 10x faster with no-code app templates

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

FlutterFlow - FlutterFlow is an online low-code platform that empowers people to build native mobile apps visually.

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

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