Software Alternatives, Accelerators & Startups

PurpleCube VS Scikit-learn

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

PurpleCube logo PurpleCube

PurpleCube is a cloud-based AI and ML data analytics platform that allows users to easily and quickly analyze complex data sets without requiring any data science or coding skills.

Scikit-learn logo Scikit-learn

scikit-learn (formerly scikits.learn) is an open source machine learning library for the Python programming language.
  • PurpleCube Landing page
    Landing page //
    2023-09-20
  • Scikit-learn Landing page
    Landing page //
    2022-05-06

PurpleCube videos

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Scikit-learn videos

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 PurpleCube and Scikit-learn)
Business & Commerce
100 100%
0% 0
Data Science And Machine Learning
Development
100 100%
0% 0
Data Science Tools
0 0%
100% 100

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Reviews

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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...

Social recommendations and mentions

Based on our record, Scikit-learn seems to be more popular. It has been mentiond 28 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.

PurpleCube mentions (0)

We have not tracked any mentions of PurpleCube yet. Tracking of PurpleCube recommendations started around Mar 2022.

Scikit-learn mentions (28)

  • 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 / 3 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 / 11 months 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
  • Help on using R for Machine Learning?
    Scikit-learn is a machine learning library that comes with a number of pre-built machine learning models, which can then be used as python wrappers. Source: about 1 year ago
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What are some alternatives?

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

IBM ILOG CPLEX Optimization Studio - IBM ILOG CPLEX Optimization Studio is an easy-to-use, affordable data analytics solution for businesses of all sizes who want to optimize their operations.

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

RapidMiner Studio - Visual workflow designer for predictive analytics that brings data science and machine learning to everyone on the analytics team

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

Jupyter - Project Jupyter exists to develop open-source software, open-standards, and services for interactive computing across dozens of programming languages. Ready to get started? Try it in your browser Install the Notebook.

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