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Topic #45

Mathematics

The main branches of Mathematics involved in Machine Learning are:

  • Linear Functions
  • Linear Graphics
  • Linear Algebra
  • Probability
  • Statistics

Machine Learning = Mathematics

Behind every ML success there is Mathematics.

All ML models are constructed using solutions and ideas from math.

The purpose of ML is to create models for understanding thinking.

If you want an ML career:

  • Data Scientist
  • Machine Learning Engineer
  • Robot Scientist
  • Data Analyst
  • Natural Language Expert
  • Deep Learning Scientist

You should focus on the mathematic concepts described here.


Linear Functions

  • Linear means straight
  • A linear function is a straight line
  • A linear graph represents a linear function

Graphics

  • Graphics plays an important role in Math
  • Graphics plays an important role in Statistics
  • Graphics plays an important role in Machine Learning

Learn more about linear functions ...


Linear Algebra

Linear algebra is the bedrock of data science.

Knowing linear algebra boosts your ability to understand data science algorithms.

Col 1 Col 2 Col 3 Col 4 Col 5
Scalar Vector(s)
1 1 2 3 1 2 3
1 2 3 1 2 3
1
2
3
1 2 3
Matrix Tensor
1 2 3 4 5 6 Tensor 1 2 3 4 5 6 4 5 6 1 2 3 End Table
1 2 3
4 5 6
1 2 3 4 5 6 4 5 6 1 2 3
1 2 3
4 5 6
4 5 6
1 2 3

Learn more about linear algebra ...


Probability

Probability is how likely something is to occur, or how likely something is true.

I have 6 balls in a bag: 3 reds, 2 are green, and 1 is blue.

Blindfolded. What is the probability that I pick a green one?

Number of ways it can happen are 2 (there are 2 greens).

Number of outcomes are 6 (there are 6 balls).

The probability is 2 out of 6: 2/6 = 0.333333...

Probability = Ways / Outcomes

Learn more about probability ...


Statistics

Statistics is about how to collect, analyze, interpret, and present data.

Statistics works with questions like:

  • What is the most Common?
  • What is the most Expected?
  • What is the most Normal?

Learn more about statistics ...

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Mathematics – FAQs

Quick answers about learning Mathematics in AI.

This free note from CodingNow 2.0 explains Mathematics in AI — concept, syntax and worked code examples you can copy, run and revise before interviews.
Yes. Every AI topic on CodingNow 2.0, including Mathematics, is 100% free with no signup required.
With focused practice, most students grasp Mathematics in 1–3 days from these notes; pairing it with CodingNow 2.0's mentor-led course takes you to job-ready depth faster.
Use the code examples in this note, then ask doubts for free on the CodingNow 2.0 Community (/community) — expert instructors answer within 24 hours.
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