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Fathom Analytics VS Scikit-learn

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

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Fathom Analytics logo Fathom Analytics

Simple, trustworthy website analytics (finally)

Scikit-learn logo Scikit-learn

scikit-learn (formerly scikits.learn) is an open source machine learning library for the Python programming language.
  • Fathom Analytics Landing page
    Landing page //
    2022-12-16
  • Scikit-learn Landing page
    Landing page //
    2022-05-06

Fathom Analytics features and specs

  • Privacy-Focused
    Fathom Analytics prides itself on being privacy-focused, ensuring that user data is not sold or shared, and complies with privacy laws such as GDPR, CCPA, and PECR.
  • Simplicity
    The platform offers a user-friendly interface that's easy to navigate and understand, making it accessible for users who might not be familiar with complex analytics software.
  • Fast Setup
    Fathom Analytics boasts a quick and straightforward setup process, allowing users to start tracking their website's data within minutes.
  • Lightweight Script
    The tracking script Fathom uses is lightweight, ensuring that it doesn't significantly slow down your website's load times.
  • Data Ownership
    Users have full ownership and control over their data, providing peace of mind about how information is managed and used.
  • Transparent Pricing
    Fathom offers clear and competitive pricing without hidden fees, making budgeting for analytics services straightforward.

Possible disadvantages of Fathom Analytics

  • Limited Features
    Compared to more comprehensive analytics platforms like Google Analytics, Fathom Analytics offers fewer features, which might not meet the needs of users who require in-depth analysis.
  • Customization
    There are fewer customization options available for reports and dashboards, limiting the ability to tailor the platform to specific business needs.
  • Integration
    Fathom Analytics lacks extensive integration capabilities, which can be a drawback for users who rely on seamless integration with a wide variety of tools.
  • Market Penetration
    Being a relatively newer and smaller player in the web analytics market, Fathom Analytics has less brand recognition and fewer community resources compared to giants like Google Analytics.

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.

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.

Fathom Analytics videos

+ Add

FATHOM ANALYTICS REVIEW 🌟 INSTALL 💸 $100 (OPEN SOURCE)

More videos:

  • Review - Fathom Analytics, One-Click DigitalOcean installation guide

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 Fathom Analytics and Scikit-learn)

Fathom Analytics

Scikit-learn

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

Fathom Analytics Reviews

Top 5 Plausible Analytics Alternatives in 2024
This differentiates Fathom Analytics from alternatives that collect vast amounts of customers’ personal information.
Source: www.putler.com
Top 9 Plausible Analytics alternatives in 2024
Fathom Analytics is known for its emphasis on privacy, providing website analytics without invasive tracking methods. It maintains user data integrity, ensuring compliance with regulations like GDPR.
Source: usermaven.com

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, Fathom Analytics should be more popular than Scikit-learn. It has been mentiond 60 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.

Fathom Analytics mentions (60)

  • 10 of the Best Web Analytics Tools for React Websites
    Marketed as the simple, lightweight, privacy-first alternative to Google Analytics, Fathom provides essential insights into website traffic and visitor behavior without compromising user privacy. - Source: dev.to / 2 months ago
  • SEO tools I used to grow my sites to 20k+ visitors/month
    Fathom is privacy first analytics for the web. According to their site, Fathom is a Google Analytics alternative that doesn’t compromise visitor privacy for data. We revolutionized website analytics by making them easy to use and respectful of privacy laws (like GDPR and more). - Source: dev.to / 5 months ago
  • Tell HN: My Favorite Tools
    A few apps that are a joy to use: https://ia.net/writer for writing. https://usecontrast.com/ for checking contrast. https://sipapp.io/ for picking colors. https://nova.app/ for editing code. https://cleanshot.com/ for screenshots. https://getpixelsnap.com/ for measuring elements on screen. https://netnewswire.com/ for reading things via RSS. https://panic.com/transmit/ for file transfers. https://usefathom.com/... - Source: Hacker News / over 1 year ago
  • 11 Ways to Optimize Your Website
    There are many good, lightweight, and open-source alternatives to Google Analytics, such as Plausible, Matomo, Fathom, Simple Analytics, and so on. Many of these options are open-source, and can be self-hosted. - Source: dev.to / over 1 year ago
  • Ask HN: Is Google Analytics that useful?
    Have you looked at Fathom[0] or GoatCounter? [0] https://usefathom.com/ [1] https://www.goatcounter.com/. - Source: Hacker News / over 1 year ago
View more

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 / 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 / 12 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

What are some alternatives?

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

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.

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.

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

Simple Analytics - The privacy-first Google Analytics alternative located in Europe.

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

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