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Data Science & ML track

Supervised Learning

Labeled learning, algorithms landscape and when each family applies.

6 concepts1 challenges
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Concepts

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1

Supervised Learning Overview

Concept · Hands-on lab included

2

Classification vs Regression

Concept · Hands-on lab included

3

Linear Models for Classification

Concept · Hands-on lab included

4

K-Nearest Neighbors

Concept · Hands-on lab included

5

Support Vector Machines

Concept · Hands-on lab included

6

Choosing Among Supervised Models

Concept · Hands-on lab included

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Next modules

Keep your learning streak going with related modules.

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Mathematics

Linear algebra, calculus and notation needed for machine learning.

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Statistics

Distributions, estimators, hypothesis testing and statistical inference.

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Python

Scientific Python stack: environments, typing, numpy-style thinking.

DevOpsForge - Data Science & ML · Supervised Learning
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