Software Alternatives, Accelerators & Startups
Register | Login

Scikit-learn VS Alteryx

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

Electe
Discover Electe, our data analytics platform dedicated to SMEs. Don't let your data go unused, take your business into the future! 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.

Alteryx logo Alteryx

Alteryx provides an indispensable and easy-to-use analytics platform for enterprise companies making critical decisions that drive their business strategy and growth.
  • Scikit-learn Landing page
    Landing page //
    2022-05-06
  • Alteryx Landing page
    Landing page //
    2023-07-15

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.

Alteryx features and specs

  • User-Friendly Interface
    Alteryx has a drag-and-drop interface that makes it easy for users to build workflows without needing extensive coding knowledge.
  • Robust Data Integration
    Alteryx can connect to a wide variety of data sources, including cloud services, databases, and flat files, enabling comprehensive data integration capabilities.
  • Advanced Analytics
    Alteryx provides advanced analytics features such as predictive analytics, spatial analytics, and statistical analysis tools.
  • Automation
    Users can automate complex data processes and workflows, saving time and increasing productivity.
  • Extensive Community and Support
    Alteryx has a strong community and a plethora of online resources, including tutorials, forums, and customer support, which can be invaluable for problem-solving and learning.

Possible disadvantages of Alteryx

  • High Cost
    Alteryx can be expensive, particularly for small to medium-sized businesses, making it less accessible for organizations with limited budgets.
  • Learning Curve
    Despite its user-friendly interface, there is still a learning curve associated with mastering Alteryx's full range of features, particularly advanced analytics.
  • Resource Intensive
    Running large or complex workflows in Alteryx can be resource-intensive, requiring significant computational power and memory.
  • Limited Real-Time Data Processing
    Alteryx is not optimized for real-time data processing, which can be a limitation for use cases requiring real-time analytics.
  • Dependency on Other Tools
    For certain functions such as visualizations, users may need to rely on other tools like Tableau or Power BI, as Alteryx's built-in visualization capabilities are limited.

Scikit-learn videos

+ Add

Learning Scikit-Learn (AI Adventures)

More videos:

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

Alteryx videos

+ Add

Why Alteryx?

More videos:

  • Review - Alteryx: The best analytics program in 2018?
  • Tutorial - Alteryx vs Excel | Alteryx Excel | Alteryx Tutorial | Alteryx for Beginners

Category Popularity

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

Scikit-learn

Alteryx

Data Science And Machine Learning
100 100%
Data Science And Machine Learning
0% 0
Data Dashboard
25 25%
Data Dashboard
75% 75
Data Science Tools
100 100%
Data Science Tools
0% 0
Business Intelligence
0 0%
Business Intelligence
100% 100

User comments

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

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

Alteryx Reviews

Top 5 AWS Glue Alternatives: Best ETL Tools
Alteryx provides its own proprietary format, i.e., data that is ordered and stored according to a particular encoding scheme designed by the company, which is not disclosed. Hence, exporting your results to a different visualization program like Tableau or Microsoft Excel is not possible.
Source: hevodata.com
The 16 Best Data Science and Machine Learning Platforms for 2021
Description: Alteryx offers data science and machine learning functionality via a suite of software products. Headlined by Alteryx Designer which automates data preparation, data blending, reporting, predictive analytics, and data science, the self-service platform touts more than 260 drag-and-drop building blocks. Alteryx lets users see variable relationships and...
Source: solutionsreview.com

Social recommendations and mentions

Based on our record, Scikit-learn seems to be more popular. It has been mentiond 31 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

Alteryx mentions (0)

We have not tracked any mentions of Alteryx yet. Tracking of Alteryx recommendations started around Mar 2021.

What are some alternatives?

When comparing Scikit-learn and Alteryx, 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.

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.

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

QlikSense - A business discovery platform that delivers self-service business intelligence capabilities

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

Qlik - Qlik offers an Active Intelligence platform, delivering end-to-end, real-time data integration and analytics cloud solutions to close the gaps between data, insights, and action.

Loading...