Software Alternatives, Accelerators & Startups
Register | Login

Scikit-learn VS Baserow

Compare Scikit-learn VS Baserow and see what are their differences

Momen
Build powerful web apps, and create your custom AI apps, no code needed! 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

Scikit-learn logo Scikit-learn

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

Baserow logo Baserow

Open source no-code database and Airtable alternative. Create your own online database without technical experience. Performant with high volumes of data, can be self hosted and supports plugins
  • Scikit-learn Landing page
    Landing page //
    2022-05-06
  • Baserow
    Image date //
    2024-01-24

Baserow is a collaborative open source no-code tool. Our job is to help you connect all your data across your teams and workflows to keep everything in sync and get the job done with a greater speed and security. The platform enables non-technical teams to digitize workflows, automate processes and improve business efficiencies.

Baserow organizes all your data into tables that are easy to create, collaborate on and look through. When there’s one database for all workflows running in your company, everyone knows exactly where to look for what.

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.

Baserow features and specs

  • Database
  • Web application
  • Filtering
  • Sorting
  • Search
  • Templates
  • Public REST API
  • API token permissions
  • Import
  • Export
  • Trash
  • Undo/redo
  • Webhooks
  • Public sharing
  • Footer aggregations
  • Row comments
  • Row coloring
  • Real time collaboration
  • Grid view
  • Gallery view
  • Kanban view
  • Form view
  • Rich field types
  • Admin panel
  • Inviting members

Scikit-learn videos

+ Add

Learning Scikit-Learn (AI Adventures)

More videos:

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

Baserow videos

+ Add

Baserow

Category Popularity

0-100% (relative to Scikit-learn and Baserow)

Scikit-learn

Baserow

Data Science And Machine Learning
100 100%
Data Science And Machine Learning
0% 0
Tech
0 0%
Tech
100% 100
Data Science Tools
100 100%
Data Science Tools
0% 0
Spreadsheets
0 0%
Spreadsheets
100% 100

User comments

Share your experience with using Scikit-learn and Baserow. 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 Scikit-learn and Baserow

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

Baserow Reviews

12 Best Open-source Database Backend Server and Google Firebase Alternatives
Baserow is a low-code and no-code database application layer with a rich REST-API headless mode for building a data-rich web and mobile apps.It features a multi-project (app) support, dynamic data tables view with a rich control panel which comes with Kanban and Calendar views as well. It supports real-time collaboration and unlimited data row display.Baserow is built on top...
Source: medevel.com

Social recommendations and mentions

Based on our record, Baserow should be more popular than Scikit-learn. It has been mentiond 96 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.

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
View more

Baserow mentions (96)

  • Why Do Developers Struggle with Low-Code? (6 Tools That Actually Help)
    4. Baserow (An Open-Source Airtable Alternative for Easy Data Management). - Source: dev.to / 2 months ago
  • Open-Source Alternative to Airtable
    I don't know of any OSS low code dbs with access controls, but baserow's paid plans do https://baserow.io/. - Source: Hacker News / about 1 year ago
  • Baserow – Self Hosted Airtable Alternative Launches No-Code Application Builder
    Hey, I'm one of the founders of Baserow. We launched the beta of our application builder last week. It allows you to build database-driven websites, web applications, and portals. It's in the same product as our database module, and will work seamlessly together with it. More information can be found in the release blog post linked to this post, and in this video https://www.youtube.com/watch?v=yjE7gxkPlDs. Even... - Source: Hacker News / about 1 year ago
  • Show HN: Teable – Open-Source No-Code Database Fusion of Postgres and Airtable
    What are the main differences compared to Baserow (https://baserow.io/)? - Source: Hacker News / about 1 year ago
  • Show HN: Teable – Open-Source No-Code Database Fusion of Postgres and Airtable
    Baserow[0] is really good! [0]: https://baserow.io/. - Source: Hacker News / about 1 year ago
View more

What are some alternatives?

When comparing Scikit-learn and Baserow, you can also consider the following products

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

NocoDB - The Open Source Airtable alternative

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

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

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

Rows - The spreadsheet where teams work faster

Loading...