
PyTorch
Keras
IBM Watson Studio
Scikit-learn
Azure Machine Learning Service
Azure Machine Learning Studio
Amazon SageMaker
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.

Swing2App
Publisheet
SpreadsheetConverter.com
Outgrow
AppSheet
Appizy
Niftyflow.rocks
SpreadsheetWEB is a no-code platform that helps businesses translate their collective Microsoft Excel expertise into robust web applications with limited or no reliance on IT resources.

Which is more popular?
Based on our record, TensorFlow seems to be more popular. It has been mentioned 8 times since March 2021.
Website, pricing, platforms and company facts side by side.
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| Website | tensorflow.org | spreadsheetweb.com |
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| Company | — | Startup from the United States · 2006 |
| Listed in |
In their own words, as submitted to SaaSHub.


No description of TensorFlow yet.
Pagos helps businesses translate their collective Microsoft Excel expertise into robust web applications with limited reliance on IT resources. The SpreadsheetWEB platform empowers ordinary Excel users to create secure, responsive, database-driven applications directly from their Excel...
What each product offers, as listed by its team.


Possible disadvantages
Walkthroughs and reviews on video.
What is Tensorflow? - Learn Tensorflow for Machine Learning and Neural Networks
More videos
Create an App with SpreadsheetWeb: Timesheets
How often each product is chosen within a category, 0–100% relative to the other.


As answered by people managing TensorFlow and SpreadsheetWEB.
SpreadsheetWEB's answer:
SpreadsheetWeb enables users to transform complex Excel spreadsheets into secure, interactive web applications without coding, combining ease of use, powerful customization, and robust security.
SpreadsheetWEB's answer:
SpreadsheetWeb uniquely combines the power and flexibility of Excel with the accessibility and security of web-based applications, enabling users to convert complex spreadsheets into secure, interactive web apps without any coding. Unlike competitors, SpreadsheetWeb supports a comprehensive array of Excel features: including over 500 Excel formulas, conditional logic, LAMBDA, Power Query, and dynamic visualizations, preserving existing spreadsheet logic seamlessly. Additionally, its robust security infrastructure, extensive customization, and powerful API integration capabilities make it the optimal choice for businesses seeking a scalable, enterprise-grade solution to manage spreadsheet proliferation, automate workflows, and centralize data securely, all while maintaining Excel’s ease of use.
SpreadsheetWEB's answer:
SpreadsheetWeb's primary audience consists of business professionals and organizations that rely heavily on complex Excel models and require a secure, scalable, and user-friendly way to transition their spreadsheets into web-based applications without coding. This includes financial analysts, actuaries, product managers, sales teams, risk management professionals, and compliance officers who regularly handle intricate formulas, data calculations, or regulatory processes. Additionally, SpreadsheetWeb appeals strongly to enterprises seeking centralized data management, security, and integration capabilities to streamline workflows, reduce spreadsheet proliferation, enhance collaboration, and enforce regulatory compliance efficiently across their organizations.
SpreadsheetWEB's answer:
SpreadsheetWeb, developed by Pagos, Inc. in 2006, was created to help businesses convert Excel-based models into secure, scalable web applications without the need for coding. Originating from the financial and insurance sectors, where Excel is heavily relied upon, it addressed challenges like version control, lack of access management, and IT bottlenecks. Unlike other no-code platforms, SpreadsheetWeb preserves the original spreadsheet logic, enabling business users to build web applications directly from Excel files while incorporating features like role-based access, workflow automation, and API integration. Over time, it has evolved to support both cloud and on-premise deployments and is now used across industries such as healthcare, insurance, manufacturing, and consulting to digitize processes, enhance security, and reduce reliance on custom software development.
SpreadsheetWEB's answer:
SpreadsheetWeb is primarily built using Microsoft .NET technologies, with ASP.NET serving as the backbone for web application development and C# as the core programming language. It leverages Microsoft Excel as the logic engine, allowing native spreadsheet formulas and functions to drive web-based applications. The platform uses SQL Server for data storage and management, and integrates with other systems via RESTful APIs. On the front end, it employs standard web technologies like HTML, CSS, and JavaScript, and supports custom UI design through a drag-and-drop interface. For deployments, it offers options across cloud, private cloud, and on-premise environments, ensuring flexibility and security for various enterprise needs.
Share your experience with using TensorFlow and SpreadsheetWEB. For example, how are they different and which one is better?
External articles and on-site reviews we used to compare the two products.


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...
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...
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...
We have no reviews of SpreadsheetWEB yet. Be the first one to post
Recommendations tracked on public social media and blogs since March 2021.


The open-source movement offers hope here. Projects like Hugging Face are democratizing access to state-of-the-art models, while initiatives like Google's TensorFlow provide powerful frameworks without licensing costs. But even... - Source: dev.to / 8 months ago
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... - Source: dev.to / almost 4 years ago
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: over 4 years ago
Tracking SpreadsheetWEB since Mar 2021.
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