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Spreadsheet.com VS Scikit-learn

Compare Spreadsheet.com VS Scikit-learn and see what are their differences

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Spreadsheet.com logo Spreadsheet.com

Spreadsheets that come alive as applications

Scikit-learn logo Scikit-learn

scikit-learn (formerly scikits.learn) is an open source machine learning library for the Python programming language.
  • Spreadsheet.com Landing page
    Landing page //
    2023-07-08
  • Scikit-learn Landing page
    Landing page //
    2022-05-06

Spreadsheet.com features and specs

  • Familiar Interface
    Spreadsheet.com retains the familiar spreadsheet interface, making it easy for users who are accustomed to traditional spreadsheets to adopt.
  • Database Functionality
    Offers database-style functionalities, such as forms and linked worksheets, allowing users to manage structured data more efficiently.
  • Customizable Workflows
    Users can create custom workflows using automation and data modeling features to suit specific project or organizational needs.
  • Collaboration Features
    Real-time collaboration tools and sharing options make it easy for teams to work together on projects from anywhere.
  • Integration Capabilities
    Integrates with various popular third-party applications, expanding its functionality and utility in diverse work environments.

Possible disadvantages of Spreadsheet.com

  • Learning Curve
    Users may experience a learning curve due to the additional functionalities compared to traditional spreadsheets.
  • Performance
    Complex or very large datasets can sometimes impact performance, slowing down the responsiveness of the application.
  • Cost
    While there is a free version, some advanced features are limited to paid plans, which may not be cost-effective for all users.
  • Limited Offline Functionality
    Spreadsheet.com relies heavily on an internet connection, with limited offline functionality, which can be restrictive in areas with poor connectivity.
  • Feature Overlap
    The range of features provided may overlap with other dedicated tools like databases and project management software, causing redundancy issues.

Scikit-learn features and specs

  • Ease of Use
    Scikit-learn provides a high-level interface for common machine learning algorithms, making it easy for beginners and professionals to implement complex models with minimal coding.
  • Extensive Documentation and Community Support
    The library has comprehensive documentation and a large, active community. This makes it easy to find tutorials, examples, and solutions to common problems.
  • Integration with Other Libraries
    Scikit-learn integrates well with other scientific computing libraries such as NumPy, SciPy, and pandas, allowing for seamless data manipulation and analysis.
  • Variety of Algorithms
    It offers a wide array of machine learning algorithms for tasks such as classification, regression, clustering, and dimensionality reduction.
  • Performance
    Designed with performance in mind, many of the algorithms are optimized and some even support multicore processing.

Possible disadvantages of Scikit-learn

  • Limited Deep Learning Support
    Scikit-learn is primarily focused on traditional machine learning algorithms and does not offer support for deep learning models, unlike libraries like TensorFlow or PyTorch.
  • Not Ideal for Large-Scale Data
    While Scikit-learn performs well for moderate-sized datasets, it may not be the best choice for extremely large datasets or big data applications.
  • Lack of Online Learning Algorithms
    The library has limited support for online learning algorithms, which are useful for scenarios where data arrives in a stream and model needs to be updated incrementally.
  • Less Flexibility in Customization
    It can be less flexible compared to lower-level libraries when highly customized or specific implementations are needed.
  • Dependency Overhead
    Scikit-learn relies on several other Python libraries like NumPy and SciPy, which might require users to manage multiple dependencies.

Spreadsheet.com videos

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Full Overview of Spreadsheet.com

Scikit-learn videos

+ Add

Learning Scikit-Learn (AI Adventures)

More videos:

  • Review - Python Machine Learning Review | Learn python for machine learning. Learn Scikit-learn.

Category Popularity

0-100% (relative to Spreadsheet.com and Scikit-learn)

Spreadsheet.com

Scikit-learn

Spreadsheets
100 100%
Spreadsheets
0% 0
Data Science And Machine Learning
0 0%
Data Science And Machine Learning
100% 100
Productivity
100 100%
Productivity
0% 0
Data Science Tools
0 0%
Data Science Tools
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 Spreadsheet.com and Scikit-learn

Spreadsheet.com Reviews

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Scikit-learn Reviews

15 data science tools to consider using in 2021
Scikit-learn is an open source machine learning library for Python that's built on the SciPy and NumPy scientific computing libraries, plus Matplotlib for plotting data. It supports both supervised and unsupervised machine learning and includes numerous algorithms and models, called estimators in scikit-learn parlance. Additionally, it provides functionality for model...
Source: searchbusinessanalytics.techtarget.com

Social recommendations and mentions

Based on our record, Scikit-learn seems to be a lot more popular than Spreadsheet.com. While we know about 31 links to Scikit-learn, we've tracked only 2 mentions of Spreadsheet.com. 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.

Spreadsheet.com mentions (2)

  • HELP! Does Trello Suck? Want to Move Away from Monday.com
    Just looked at spreadsheet.com - it's not a google product is it? I am very much attracted to the visual/graphic charts that show forecasted revenue and things of that nature. I don't know if any other program has the ability to put those up. There's only one GB of storage per workbook however, and only 1500 line items per workbook. Source: over 2 years ago
  • Rows.com: Spreadsheets on Steroids
    3. Business processes What Rows does falls mostly into the realm of small databases and business processes. And while each has their own approach, I'd say that most other "next-gen spreadsheets" are also focusing on these (big and important) use-cases. Airtable (https://airtable.com/), Spreadsheet.com (https://spreadsheet.com/) and Smartsheet (https://smartsheet.com/) all play mainly in this area. GRID is focusing... - Source: Hacker News / over 3 years ago

Scikit-learn mentions (31)

  • Must-Know 2025 Developer’s Roadmap and Key Programming Trends
    Python’s Growth in Data Work and AI: Python continues to lead because of its easy-to-read style and the huge number of libraries available for tasks from data work to artificial intelligence. Tools like TensorFlow and PyTorch make it a must-have. Whether you’re experienced or just starting, Python’s clear style makes it a good choice for diving into machine learning. Actionable Tip: If you’re new to Python,... - Source: dev.to / 3 months ago
  • 🚀 Launching a High-Performance DistilBERT-Based Sentiment Analysis Model for Steam Reviews 🎮🤖
    Scikit-learn (optional): Useful for additional training or evaluation tasks. - Source: dev.to / 5 months ago
  • Essential Deep Learning Checklist: Best Practices Unveiled
    How to Accomplish: Utilize data splitting tools in libraries like Scikit-learn to partition your dataset. Make sure the split mirrors the real-world distribution of your data to avoid biased evaluations. - Source: dev.to / 11 months ago
  • How to Build a Logistic Regression Model: A Spam-filter Tutorial
    Online Courses: Coursera: "Machine Learning" by Andrew Ng EdX: "Introduction to Machine Learning" by MIT Tutorials: Scikit-learn documentation: https://scikit-learn.org/ Kaggle Learn: https://www.kaggle.com/learn Books: "Hands-On Machine Learning with Scikit-Learn, Keras & TensorFlow" by Aurélien Géron "The Elements of Statistical Learning" by Trevor Hastie, Robert Tibshirani, and Jerome Friedman By... - Source: dev.to / about 1 year ago
  • Link Prediction With node2vec in Physics Collaboration Network
    Firstly, we need a connection to Memgraph so we can get edges, split them into two parts (train set and test set). For edge splitting, we will use scikit-learn. In order to make a connection towards Memgraph, we will use gqlalchemy. - Source: dev.to / almost 2 years ago
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What are some alternatives?

When comparing Spreadsheet.com and Scikit-learn, you can also consider the following products

Airtable - Airtable works like a spreadsheet but gives you the power of a database to organize anything. Sign up for free.

Pandas - Pandas is an open source library providing high-performance, easy-to-use data structures and data analysis tools for the Python.

Magic Spreadsheet - Human workforce and AI plugged into your Google Spreadsheets

OpenCV - OpenCV is the world's biggest computer vision library

Rows - The spreadsheet where teams work faster

NumPy - NumPy is the fundamental package for scientific computing with Python

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