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Machine Learning & Data Science · head to head

MATLAB vs scikit-learn

MATLAB logo

MATLAB

Machine Learning & Data Science

Programming and numeric computing platform

From
$99/month
Rated
-
Full reviewWebsite
S

scikit-learn

Machine Learning & Data Science

Machine learning in Python

From
Free
Rated
-
Full reviewWebsite

The short version

  • Only scikit-learn has a free tier, so it costs nothing to try first.
  • Each has a real cost: MATLAB a standard individual licence is $940 a year, and it is annual rather than perpetual; scikit-learn no GPU acceleration by default; limited optional GPU support requires external arrays
  • They diverge on capability: MATLAB covers Matrix computations, scikit-learn covers Classification algorithms.

Where they differ

Only the attributes on which MATLAB and scikit-learn actually diverge.

Attributes where MATLAB and scikit-learn differ
AttributeMATLABscikit-learn
Starting price$99/monthFree
Pricing modelsubscriptionUnknown
Free tierNoYes
PlatformsLinux, Mac, WindowsPython, Linux, macOS, Windows
Founded19842007

Identical on both: user rating (Not yet rated), category (Machine Learning & Data Science).

What each one covers

Drawn from each product's published feature list. An absence here means we hold no record of it - not that the product lacks it.

Only in MATLAB

  • Matrix computations
  • Data visualization
  • Machine learning
  • Deep learning
  • Signal processing
  • Simulink
  • Python
  • C/C++

Only in scikit-learn

  • Classification algorithms
  • Regression models
  • Clustering methods
  • Dimensionality reduction
  • Model selection
  • NumPy
  • SciPy
  • Pandas

Both cover

  • Linux support
  • Mac support
  • Windows support

What people use each for

The jobs each tool is most often brought in to do.

MATLAB

  • Numerical computing, simulation and algorithm developmentnot scikit-learn
  • Engineering and scientific modelling with Simulinknot scikit-learn

scikit-learn

  • Machine learningnot MATLAB
  • Data analysisnot MATLAB
  • Model trainingnot MATLAB
  • Predictive analyticsnot MATLAB

Where each one falls short

Documented limitations, not opinions. Every one is a constraint you would hit in normal use.

MATLAB

  • A standard individual licence is $940 a year, and it is annual rather than perpetual
  • Add on toolboxes are bought separately through the web store rather than being included
  • No price is displayed for the academic, student, home or startup licences, each of which requires a quote
  • Eligibility rather than price separates most tiers, so a commercial user has one option

scikit-learn

  • No GPU acceleration by default; limited optional GPU support requires external arrays
  • Single-machine only; no built-in distributed computing across clusters
  • All datasets must fit entirely in RAM; no out-of-core learning
  • No production-grade deep learning; neural network support limited to basic multilayer perceptron
  • No reinforcement learning algorithms

Pricing, plan by plan

MATLAB

$99/month
  • Home$149/perpetual
    • Personal use
    • Core MATLAB
  • Standard$2350/perpetual
    • Commercial use
    • Full features

scikit-learn

Free

No published plan breakdown. See the scikit-learn review.

Which should you pick?

Choose MATLAB if

  • You need matrix computations.
  • You work on Linux, Mac, Windows.
  • You also want data visualization.
MATLAB review

Choose scikit-learn if

  • You need classification algorithms.
  • You want to start without paying.
  • You work on Python, Linux, macOS, Windows.
  • You also want regression models.
scikit-learn review

Questions people ask

Is MATLAB or scikit-learn better?
Neither clearly leads. MATLAB starts at $99/month and scikit-learn at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, MATLAB or scikit-learn?
scikit-learn has a free tier; the other does not. Paid plans start at $99/month for MATLAB and Free for scikit-learn.
Does MATLAB or scikit-learn run on more platforms?
MATLAB runs on Linux, Mac, Windows. scikit-learn runs on Python, Linux, macOS, Windows.
Can I use scikit-learn for free?
Yes. scikit-learn has a free tier, so you can try it without paying. MATLAB starts at $99/month.
What is MATLAB best used for?
MATLAB is most often used for numerical computing, simulation and algorithm development, engineering and scientific modelling with simulink. Of those, numerical computing, simulation and algorithm development and engineering and scientific modelling with simulink are not what scikit-learn is typically brought in for.
What can MATLAB do that scikit-learn cannot?
MATLAB covers Matrix computations, Data visualization, Machine learning, Deep learning. scikit-learn covers Classification algorithms, Regression models, Clustering methods, Dimensionality reduction. Both handle Linux support, Mac support, Windows support.

Answered from the vendors’ own pages

scikit-learn: Does scikit-learn support GPU acceleration?

Scikit-learn has no native GPU support by design to keep installation simple and cross-platform. Since 2023, a limited number of estimators can run on GPUs if input data is provided as PyTorch or CuPy arrays, but this requires additional setup.

Source
scikit-learn: Can scikit-learn handle datasets larger than RAM?

No. Scikit-learn is built on NumPy which requires all data to fit in memory, and NumPy operates on single-machine CPUs only. For very large datasets, consider Spark MLlib or distributed alternatives.

Source
scikit-learn: Is scikit-learn free to use commercially?

Yes. Scikit-learn is open source under the BSD license, which allows free commercial use, modification, and distribution.

Source
scikit-learn: What neural network capabilities does scikit-learn have?

Scikit-learn includes only a basic multilayer perceptron (MLPClassifier and MLPRegressor) for simple feedforward networks. For serious deep learning, use PyTorch, TensorFlow, or Keras instead.

Source
scikit-learn: Does scikit-learn include natural language processing?

Scikit-learn has minimal NLP support limited to basic text feature extraction and vectorization. For comprehensive text processing, use spaCy or NLTK instead.

Source
scikit-learn: When was scikit-learn first released?

Scikit-learn's first public release was February 1, 2010, following its start as a Google Summer of Code project in 2007.

Source
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