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Moving window for Time Series Data

Instructor: Applied AI Course Duration: 25 mins

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Introduction

Fourier decomposition

Featurization and Feature engineering.

1.1

17 min

1.2

Moving window for Time Series Data

25 min

1.3

Fourier decomposition

22 min

1.4

Deep learning features: LSTM

8 min

1.5

Image histogram

23 min

1.6

Keypoints: SIFT.

10 min

1.7

Deep learning features: CNN

4 min

1.8

Relational data

10 min

1.9

12 min

1.10

Indicator variables

7 min

1.11

Feature binning

14 min

1.12

Interaction variables

8 min

1.13

Mathematical transforms

4 min

1.14

Model specific featurizations

3 min

1.15

Feature orthogonality

11 min

1.16

Domain specific featurizations

4 min

1.17

Feature slicing

10 min

1.18

Kaggle Winners solutions

7 min