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IBM SPSS Statistics VS Scikit-learn

Compare IBM SPSS Statistics VS Scikit-learn and see what are their differences

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LibHunt tracks mentions of software libraries on relevant social networks. Based on that data, you can find the most popular projects and their alternatives. featured
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  4. » Alternatives

IBM SPSS Statistics logo IBM SPSS Statistics

IBM SPSS Statistics is software that provides detailed analysis of statistical data. The company behind the product practically needs no introduction, as it's been a staple of the technology industry for over 100 years.

Scikit-learn logo Scikit-learn

scikit-learn (formerly scikits.learn) is an open source machine learning library for the Python programming language.
  • IBM SPSS Statistics Landing page
    Landing page //
    2023-09-16
  • Scikit-learn Landing page
    Landing page //
    2022-05-06

IBM SPSS Statistics videos

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IBM SPSS Statistics Overview

More videos:

  • Review - What's new in IBM SPSS Statistics 26

Scikit-learn videos

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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 IBM SPSS Statistics and Scikit-learn)

IBM SPSS Statistics

Scikit-learn

Technical Computing
100 100%
Technical Computing
0% 0
Data Science And Machine Learning
0 0%
Data Science And Machine Learning
100% 100
Data Dashboard
51 51%
Data Dashboard
49% 49
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 IBM SPSS Statistics and Scikit-learn

IBM SPSS Statistics Reviews

Top 7 Predictive Analytics Tools
IBM SPSS Statistics is a popular predictive analytics tool. It offers a user-friendly interface and a strong set of features including the SPSS modeler, which provides advanced statistical procedures, helps ensure precision, and provides positive decision-making. All of the analytics lifecycle features are included, such as data preparation and management to analysis and...
Source: www.datamation.com
Top 10 Free Statistical Analysis Software 2023
IBM SPSS Statistics is a popular statistical software package that is widely used in academia, research, and industry for data analysis, reporting, and visualization. Some of the key features of IBM SPSS Statistics include:
Source: fellowshipbard.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, Scikit-learn seems to be more popular. It has been mentiond 27 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.

IBM SPSS Statistics mentions (0)

We have not tracked any mentions of IBM SPSS Statistics yet. Tracking of IBM SPSS Statistics recommendations started around Mar 2021.

Scikit-learn mentions (27)

  • 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: 12 months 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: 12 months 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
  • Machine learning with Julia - Solve Titanic competition on Kaggle and deploy trained AI model as a web service
    This is not a book, but only an article. That is why it can't cover everything and assumes that you already have some base knowledge to get the most from reading it. It is essential that you are familiar with Python machine learning and understand how to train machine learning models using Numpy, Pandas, SciKit-Learn and Matplotlib Python libraries. Also, I assume that you are familiar with machine learning... - Source: dev.to / about 1 year ago
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What are some alternatives?

When comparing IBM SPSS Statistics and Scikit-learn, you can also consider the following products

RStudio - RStudio™ is a new integrated development environment (IDE) for R.

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

Stata - Stata is a software that combines hundreds of different statistical tools into one user interface. Everything from data management to statistical analysis to publication-quality graphics is supported by Stata. Read more about Stata.

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

JMP - JMP is a data representation tool that empowers the engineers, mathematicians and scientists to explore the any of data visually.

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

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