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Scikit-learn VS Simple Analytics

Compare Scikit-learn VS Simple Analytics and see what are their differences

LiveSession
LiveSession helps you analyze users’ behavior, improve UX, find JS bugs, and increase conversion rates using session replays, and event-based product analytics. featured
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Scikit-learn logo Scikit-learn

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

Simple Analytics logo Simple Analytics

The privacy-first Google Analytics alternative located in Europe.
  • Scikit-learn Landing page
    Landing page //
    2022-05-06
  • Simple Analytics Landing page
    Landing page //
    2022-09-05

Simple Analytics gives you insights into the performance of your website without ever collecting personal data, with a clean interface, and simple integration. GDPR, CCPA and, PECR compliant because we don't handle personal data and set no cookies.

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.

Simple Analytics features and specs

  • Privacy-focused
    Simple Analytics does not collect personal data, ensuring compliance with privacy laws like GDPR and CCPA. This approach appeals to users concerned about data privacy.
  • Ease of Use
    The platform prides itself on a user-friendly interface, making analytics accessible for individuals with varying levels of technical expertise.
  • No Cookies
    By eliminating the need for cookies, Simple Analytics reduces the complexity of compliance and improves user trust.
  • Transparent Pricing
    Offers straightforward pricing without hidden fees, which benefits small to medium-sized businesses looking for cost-effective solutions.
  • Quick Setup
    Setting up Simple Analytics is a quick process, often taking just a few minutes, reducing the time and effort required to begin tracking site data.
  • Lightweight Script
    The tracking script is lightweight, ensuring that it does not significantly affect website loading times, thus maintaining a good user experience.

Possible disadvantages of Simple Analytics

  • Limited Features
    Compared to more comprehensive platforms like Google Analytics, Simple Analytics offers fewer features and customization options, which may not satisfy advanced users.
  • Basic Reporting
    The reporting capabilities are basic and may not provide in-depth insights that large enterprises or data-driven teams may require.
  • No Integration with Ad Services
    Simple Analytics lacks built-in integrations with advertising services like Google Ads, potentially complicating the tracking of campaign performance.
  • Smaller User Community
    Given its niche market focus, the platform has a smaller user community, which can make it harder to find peer support or community-driven solutions.
  • Less Mature Ecosystem
    Unlike older platforms, Simple Analytics may lack integrations with a wide range of third-party tools and services, limiting its flexibility.
  • Cost
    While the pricing is transparent, it can still be seen as relatively high for the features offered, especially when compared to free alternatives like Google Analytics.

Analysis of Scikit-learn

Overall verdict

  • Yes, Scikit-learn is generally regarded as a good library for machine learning, especially for beginners and intermediate users who need reliable tools with efficient implementation of numerous algorithms.

Why this product is good

  • Scikit-learn is considered a good machine learning library because it provides a wide range of state-of-the-art algorithms for supervised and unsupervised learning. It is designed to interoperate with the Python numerical and scientific libraries NumPy and SciPy. The library is well-documented, easy to use, and has a consistent API that simplifies the integration of different algorithms. Furthermore, there's a strong community and continuous development, which means it is well-maintained and updated regularly with new features and improvements.

Recommended for

  • Beginners learning machine learning concepts and application.
  • Data scientists and engineers looking for a robust and efficient toolkit to build and deploy machine learning models.
  • Researchers who need an easy-to-use library that facilitates the experimentation of various algorithms.
  • Developers who require a seamless, Python-based machine learning library that integrates well with other data analysis tools and environments.

Analysis of Simple Analytics

Overall verdict

  • Simple Analytics is a good choice for users who prioritize privacy and simplicity in their web analytics tools. It provides sufficient insights for basic website analytics needs without overwhelming users with too much data or complex features.

Why this product is good

  • Simple Analytics is often praised for its privacy-focused approach. It does not collect personal data, which appeals to users and businesses concerned about privacy and compliance with data protection regulations like GDPR. The platform offers an easy-to-understand interface with essential analytics metrics, making it accessible to users without a technical background. Additionally, Simple Analytics is lightweight, which means it doesn't slow down websites as much as other analytics tools might.

Recommended for

    Simple Analytics is recommended for small to medium-sized businesses, bloggers, and website owners who need straightforward analytics and value privacy. It’s particularly suitable for those looking to comply with privacy regulations without compromising on user data protection.

Scikit-learn videos

+ Add

Learning Scikit-Learn (AI Adventures)

More videos:

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

Simple Analytics videos

+ Add

Fathom, simple analytics. A Google Analytics alternative | Privacy & Simplicity focused! 🎯

More videos:

  • Review - Seriously Simple Analytics Review
  • Review - Seriously Simple Analytics Review
  • Demo - Why we created Simple Analytics

Category Popularity

0-100% (relative to Scikit-learn and Simple Analytics)

Scikit-learn

Simple Analytics

Data Science And Machine Learning
100 100%
Data Science And Machine Learning
0% 0
Analytics
0 0%
Analytics
100% 100
Data Science Tools
100 100%
Data Science Tools
0% 0
Web Analytics
0 0%
Web Analytics
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 Scikit-learn and Simple Analytics

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

Simple Analytics Reviews

Top 10 AI Data Analysis Tools in 2024
Simple Analytics is a revolutionary web analytics platform that prioritizes user privacy and transparency above all else. Developed as an ethical alternative to data-hungry giants like Google Analytics, Simple Analytics offers a refreshingly lightweight and user-friendly solution for tracking website metrics without compromising on data protection. With its unwavering...
Source: powerdrill.ai
Privacy-oriented alternatives to Google Analytics
Simple Analytics was my original second contender for the analytics of this blog. The $19 a month starting plan with 100k pageviews is on the more expensive side, but their yearly deal gets you a better price than Fathom at just $9 a month.
Source: nts.strzibny.name
Lightweight alternatives to Google Analytics
One is the minimalist Simple Analytics product, which is a cloud-based tool created by solo developer Adriaan van Rossum; it has a clean-looking interface with only the few key metrics, similar to Plausible. Another is Fathom, which was open source initially, but the current version is proprietary (although the company hopes to start maintaining the open-source code base...
Source: lwn.net

Social recommendations and mentions

Scikit-learn might be a bit more popular than Simple Analytics. We know about 31 links to it since March 2021 and only 26 links to Simple Analytics. 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 / 4 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 / 6 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 / about 1 year 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 / over 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 / about 2 years ago
View more

Simple Analytics mentions (26)

  • This Next.js blog template is awesome.
    Multiple analytics options including Umami, Plausible, Simple Analytics, Posthog and Google Analytics. - Source: dev.to / 8 months ago
  • Awesome-no-code-tools
    Simple Analytics - Simple, clean, and friendly analytics. - Source: dev.to / 11 months ago
  • SaasRock v0.5.0 - Cookie consent and built-in Analytics
    SaasRock does not intend to invent the wheel, there are great analytics solutions out there, both free and powerful. But SaasRock’s main goal is to have everything you need when building SaaS applications, at least in a minimal way. - Source: dev.to / almost 3 years ago
  • Italian watchdog bans use of Google Analytics
    Regarding forbidden countries, it’s not forbidden in the Netherlands, yet. They will announce a verdict in a form of a report by the end of 2022 [1]. To give people an option and pink something else over Google Analytics, I have built an alternative, Simple Analytics [2]. It doesn’t use cookies or any form of tracking and you get still the useful data that 80% of the website owners need. [1]... - Source: Hacker News / almost 3 years ago
  • Italian watchdog bans use of Google Analytics
    It is. Most startups in the EU have to use more and more businesses in the EU. The selection is little, so way more changes to succeed if your EU based and serve both markets. I run Simple Analytics [1], which is a privacy-first analytics business from the Netherlands. I see a lot of business from the EU just because we are from the EU as well. [1] https://simpleanalytics.com/?ref=hn. - Source: Hacker News / almost 3 years ago
View more

What are some alternatives?

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

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

Plausible.io - Plausible Analytics is a simple, open-source, lightweight (< 1 KB) and privacy-friendly web analytics alternative to Google Analytics. Made and hosted in the EU, powered by European-owned cloud infrastructure 🇪🇺

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

Fathom Analytics - Simple, trustworthy website analytics (finally)

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

Google Analytics - Improve your website to increase conversions, improve the user experience, and make more money using Google Analytics. Measure, understand and quantify engagement on your site with customized and in-depth reports.

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