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Logistic regression revisited

Instructor: Applied AI Course Duration: 4 mins

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Sampling data and tags+Weighted models.

Why not use advanced techniques

Stack Overflow Tag Prediction

1.1

Business/Real world problem

10 min

1.2

Business objectives and constraints

5 min

1.3

Mapping to an ML problem: Data overview

4 min

1.4

Mapping to an ML problem:ML problem formulation.

5 min

1.5

Mapping to an ML problem:Performance metrics.

21 min

1.6

7 min

1.7

EDA:Data Loading

13 min

1.8

EDA:Analysis of tags

11 min

1.9

EDA:Data Preprocessing

11 min

1.10

Data Modeling : Multi label Classification

18 min

1.11

Data preparation.

8 min

1.12

Train-Test Split

2 min

1.13

6 min

1.14

Logistic regression: One VS Rest

7 min

1.15

Sampling data and tags+Weighted models.

4 min

1.16

Logistic regression revisited

4 min

1.17

Why not use advanced techniques

3 min

1.18

5 min