Data Science & ML track

Mathematics

Linear algebra, calculus and notation needed for machine learning.

8 concepts2 labs1 challenges
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Concepts

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1

Why Mathematics Matters

Concept · Hands-on lab included

2

Vectors and Dot Products

Concept · Hands-on lab included

3

Matrices and Multiplication

Concept · Hands-on lab included

4

Matrix Inverses and Rank

Concept · Hands-on lab included

5

Eigenvalues and Eigenvectors

Concept · Hands-on lab included

6

Derivatives and Gradients

Concept · Hands-on lab included

7

Partial Derivatives and Gradient Descent

Concept · Hands-on lab included

8

Linear Algebra and Calculus in ML

Concept · Hands-on lab included

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Hands-on labs

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