Software Alternatives, Accelerators & Startups

Scikit-learn VS Metabase

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

Scikit-learn logo Scikit-learn

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

Metabase logo Metabase

Metabase is the easy, open source way for everyone in your company to ask questions and learn from...
  • Scikit-learn Landing page
    Landing page //
    2022-05-06
  • Metabase Landing page
    Landing page //
    2023-04-25

Scikit-learn videos

Learning Scikit-Learn (AI Adventures)

More videos:

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

Metabase videos

Metabase is a free, self hosted, open source data analytics platform that keeps using it simple.

Category Popularity

0-100% (relative to Scikit-learn and Metabase)
Data Science And Machine Learning
Business Intelligence
0 0%
100% 100
Data Science Tools
100 100%
0% 0
Data Dashboard
25 25%
75% 75

User comments

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Reviews

These are some of the external sources and on-site user reviews we've used to compare Scikit-learn and Metabase

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...

Metabase Reviews

Top 11 Grafana Alternatives & Competitors [2024]
Metabase is tailored for exploring and querying structured data within databases. It empowers users with an intuitive interface to effortlessly create and share interactive dashboards, facilitating seamless data exploration. One of its notable advantages is the accessibility it offers to non-technical users, granting them the ability to create their own charts without...
Source: signoz.io
Embedded analytics in B2B SaaS: A comparison
Similar to Holistics also Metabase is a BI tool at its core. It however feels nothing like Looker and has a unique feel to it. It felt quite intuitive how its set-up but there’s still quite a steep learning curve, even for a well-seasoned data professional. Also Metabase offers an iFrame implementation for embedding. An added advantage of Metabase is that they are...
Source: medium.com
Best 8 Redash Alternatives in 2023 [In Depth Guide]
Metabase is a business intelligence software suite allowing you to ask questions about your data without complicated code and jargon and lets professionals visualize their business data accurately.
Source: www.datapad.io
8 Alternatives to Apache Superset That’ll Empower Start-ups and Small Businesses with BI
Small businesses and startups with limited resources that need to answer simple queries will find Metabase, Tableau, and PowerBI suitable for their needs. However, if you have an in-house data team dedicated to the project, you might find open-source software like Redash and Metabase (open-source version) beneficial. And if you have the team, time, and money, Looker or...
Source: trevor.io
Top 10 Tableau Open Source Alternatives: A Comprehensive List
Tableau Open Source alternatives are typically free, making them appealing to freelancers and small businesses. However, even Business Intelligence tools with a commercial component, such as Metabase, are less expensive on average. Metabase is very similar to Tableau in the sense that it is a Data Analytics tool that is accessible to both tech-savvy and non-tech-savvy users....
Source: hevodata.com

Social recommendations and mentions

Based on our record, Scikit-learn should be more popular than Metabase. It has been mentiond 29 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 (29)

  • 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 / 8 days 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 / 4 months 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 / about 1 year ago
  • WiFilter is a RaspAP install extended with a squidGuard proxy to filter adult content. Great solution for a family, schools and/or public access point
    The ML component is based on scikit-learn which differentiates it from purely list-based filters. It couples this with a full-featured wireless router (RaspAP) in a single device, so it fulfills the needs of a use case not entirely addressed by Pi-hole. Source: about 1 year ago
  • PSA: You don't need fancy stuff to do good work.
    Finally, when it comes to building models and making predictions, Python and R have a plethora of options available. Libraries like scikit-learn, statsmodels, and TensorFlowin Python, or caret, randomForest, and xgboostin R, provide powerful machine learning algorithms and statistical models that can be applied to a wide range of problems. What's more, these libraries are open-source and have extensive... Source: about 1 year ago
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Metabase mentions (14)

  • Is Tableau Dead?
    I've never used Tableau, but heard a lot of hate about it. However, in my previous role, we were big fans of Metabase (https://metabase.com). You can also self-host it, which was a huge win for us. - Source: Hacker News / 4 months ago
  • Ask HN: Open-Source Self-Hosted No-Code Platforms?
    The solution really depends on what sort of problems you are trying to solve and who your customers are. There are a fair few low-code solutions out there for reporting and data visualisation that are great for finance and marketing teams for example. e.g. https://metabase.com/ , https://evidence.dev/ For enterprise processes I'd go with Camunda (solely based on recommendations and not first hand experience).... - Source: Hacker News / about 1 year ago
  • Ask HN: Who is hiring? (December 2022)
    Metabase | https://metabase.com | REMOTE | Full-time | Backend, Frontend, Full Stack, and DevOps engineers. - Source: Hacker News / over 1 year ago
  • Make Better Decisions the Easy Way: Deploy Metabase with Azure Container Apps
    With a few simple steps, you can deploy Metabase on Microsoft Azure using Azure Container Apps. This process works for any Docker container hosted on Docker Hub, not just Metabase, so you can try it with your containers. - Source: dev.to / almost 2 years ago
  • Integration/extension/plugin system in Nodejs
    Try metabase.com its built with node and uses plugins. Source: about 2 years ago
View more

What are some alternatives?

When comparing Scikit-learn and Metabase, 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.

Tableau - Tableau can help anyone see and understand their data. Connect to almost any database, drag and drop to create visualizations, and share with a click.

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

Microsoft Power BI - BI visualization and reporting for desktop, web or mobile

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

Looker - Looker makes it easy for analysts to create and curate custom data experiences—so everyone in the business can explore the data that matters to them, in the context that makes it truly meaningful.