Generate Random Vectors

Vectors are the one-dimensional cousins of matrices — ordered lists of numbers that anchor dot products, norms, projections and most of modern machine learning. Practising with them needs a steady supply of fresh examples, and hand-picking entries never quite behaves randomly.

Generate Random Vectors produces a vector of any length up to 100, with entries drawn from any range you choose. Toggle between row-vector and column-vector notation, choose integers or decimals, and get a clean, correctly formatted result that pastes straight into homework, code or notes. Every run is a fresh draw — unlimited practice, unlimited test data, zero effort.

• Row or column notation: One toggle switches between [a, b, c] and the vertical column form.
• Length up to 100: From a 2-entry vector to a 100-dimensional one.
• Any range: Negative, fractional and huge values are all fine.
• Integers or decimals: Choose whole numbers or set the decimal precision.
• Cryptographic randomness: Fresh secure draws every run.
• Live regeneration: The vector updates instantly with every setting change.
• Copy or download: Ready for documents, spreadsheets and code.
• Free and private: Everything runs in your browser; nothing is uploaded.

1. Set the length. Choose how many entries the vector should have — up to 100.
2. Choose the range. Set minimum and maximum entry values.
3. Pick the orientation. Select "Row" for [a, b, c] or "Column" for the vertical form.
4. Decide on integers. Toggle whole numbers, or leave decimals on and set the precision.
5. Read the vector. It appears instantly in correct notation.
6. Copy or download. Take it into your document, spreadsheet or test code. Regenerate anytime for a fresh vector.

Example 1 — Dot product practice. Generate two row vectors of length 3 with small integers and compute the dot product by hand, then check with the number tools. Every run gives a fresh pair.

Example 2 — Column vectors in equations. For a linear combination exercise like x·v₁ + y·v₂, generate column vectors of length 2 or 3 and keep the vertical notation — it matches how the textbook states the problem.

Example 3 — Statistical observations. A 20-entry column vector of decimals between 0 and 1 with precision 2 reads as a realistic sample for a statistics exercise.

Example 4 — Machine learning features. Need a quick feature vector for a demo? Generate a length-32 row vector of decimals between −1 and 1 — instant plausible embedding data.

• Unlimited fresh examples: No exercise is ever reused.
• Correct notation built in: Row and column forms render the way textbooks expect.
• Full control: Length, range, type and precision are all yours.
• Test data on demand: Ready-made vectors for code and simulations.
• Instant iteration: Live regeneration makes comparisons effortless.
• Free and private: Runs entirely in the browser with nothing uploaded.