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Minitab 18 VS NumPy

Compare Minitab 18 VS NumPy and see what are their differences

LibHunt
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
Contents:
  1. » Base Details
  2. » Videos
  3. » Reviews
  4. » Alternatives

Minitab 18 logo Minitab 18

Get started with Minitab, get help using Minitab tools and features, and find definitions for common terms.

NumPy logo NumPy

NumPy is the fundamental package for scientific computing with Python
  • Minitab 18 Landing page
    Landing page //
    2022-11-10
  • NumPy Landing page
    Landing page //
    2023-05-13

Minitab 18 videos

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Crear Diagrama Causa - Efecto (Diagrama de Ishikawa) en Minitab 18 | Herramientas de calidad

NumPy videos

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Learn NUMPY in 5 minutes - BEST Python Library!

More videos:

  • Review - Python for Data Analysis by Wes McKinney: Review | Learn python, numpy, pandas and jupyter notebooks
  • Review - Effective Computation in Physics: Review | Learn python, numpy, regular expressions, install python

Category Popularity

0-100% (relative to Minitab 18 and NumPy)

Minitab 18

NumPy

Technical Computing
100 100%
Technical Computing
0% 0
Data Science And Machine Learning
0 0%
Data Science And Machine Learning
100% 100
Data Dashboard
26 26%
Data Dashboard
74% 74
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 Minitab 18 and NumPy

Minitab 18 Reviews

We have no reviews of Minitab 18 yet.
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NumPy Reviews

25 Python Frameworks to Master
SciPy provides a collection of algorithms and functions built on top of the NumPy. It helps to perform common scientific and engineering tasks such as optimization, signal processing, integration, linear algebra, and more.
Source: kinsta.com
Top 8 Image-Processing Python Libraries Used in Machine Learning
Scipy is used for mathematical and scientific computations but can also perform multi-dimensional image processing using the submodule scipy.ndimage. It provides functions to operate on n-dimensional Numpy arrays and at the end of the day images are just that.
Source: neptune.ai
Top Python Libraries For Image Processing In 2021
Numpy It is an open-source python library that is used for numerical analysis. It contains a matrix and multi-dimensional arrays as data structures. But NumPy can also use for image processing tasks such as image cropping, manipulating pixels, and masking of pixel values.
Source: www.analyticsvidhya.com
4 open source alternatives to MATLAB
NumPy is the main package for scientific computing with Python (as its name suggests). It can process N-dimensional arrays, complex matrix transforms, linear algebra, Fourier transforms, and can act as a gateway for C and C++ integration. It's been used in the world of game and film visual effect development, and is the fundamental data-array structure for the SciPy Stack,...
Source: opensource.com

Social recommendations and mentions

Based on our record, NumPy seems to be more popular. It has been mentiond 112 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.

Minitab 18 mentions (0)

We have not tracked any mentions of Minitab 18 yet. Tracking of Minitab 18 recommendations started around Mar 2021.

NumPy mentions (112)

  • Essential Deep Learning Checklist: Best Practices Unveiled
    How to Accomplish: Develop a script that iterates over the image database, preprocesses each image according to the model's requirements (e.g., resizing, normalization), and feeds them into the model for prediction. Ensure the script can handle large datasets efficiently by implementing batch processing. Use libraries like NumPy or Pandas for data management and TensorFlow or PyTorch for model inference. Include... - Source: dev.to / 4 days ago
  • Documenting my pin collection with Segment Anything: Part 3
    NumPy: This library is fundamental for handling arrays and matrices, such as for operations that involve image data. NumPy is used to manipulate image data and perform calculations for image transformations and mask operations. - Source: dev.to / 5 days ago
  • Awesome List
    NumPy - The fundamental package for scientific computing with Python. NumPy Documentation - Official documentation. - Source: dev.to / 10 days ago
  • NumPy for Beginners: A Basic Guide to Get You Started
    This guide covers the basics of NumPy, and there's much more to explore. Visit numpy.org for more information and examples. - Source: dev.to / 12 days ago
  • 2 Minutes to JupyterLab Notebook on Docker Desktop
    Below is an example of a code cell. We'll visualize some simple data using two popular packages in Python. We'll use NumPy to create some random data, and Matplotlib to visualize it. - Source: dev.to / 9 months ago
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What are some alternatives?

When comparing Minitab 18 and NumPy, 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.

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

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

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