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Keywords and identifiers

Instructor: Applied AI Course Duration: 6 mins

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2.1
Introduction to IRIS dataset

26 min
2.2
3D scatter plot

6 min
2.3
Pair plots

14 min
2.4
Limitations of Pair Plots

2 min
2.5
Histogram and Introduction to PDF(Probability Density Function)

17 min
2.6
Univariate Analysis using PDF

6 min
2.7
Mean, Variance and Standard Deviation

17 min
2.8
Median

10 min
2.9
Percentiles and Quantiles

9 min
2.10
Box-plot with Whiskers

9 min
2.11
Violin Plots

4 min
2.12
Summarizing Plots, Univariate, Bivariate and Multivariate analysis

6 min
2.13
Multivariate Probability Density, Contour Plot

9 min
2.14
Exercise: Perform EDA on Haberman dataset

4 min
3.1
Why learn it ?

4 min
3.2
Introduction to Vectors(2-D, 3-D, n-D)

14 min
3.3
Dot Product and Angle between 2 Vectors,Row Vector,Column Vector

14 min
3.4
Projection and Unit Vector

5 min
3.5
Equation of a line (2-D), Plane(3-D) and Hyperplane (n-D) - Copy

23 min
3.6
Equation of a Circle (2-D), Sphere (3-D) and Hypersphere (n-D)

7 min
3.7
Equation of an Ellipse (2-D), Ellipsoid (3-D) and Hyperellipsoid (n-D)

6 min
3.8
Square, Rectangle

6 min
3.9
Hyper-cube and Hyper-cuboid

3 min