PCA | Principal Component Analysis | Theory

[@FurqanKhan1828]

Amazing lecture

[@Crafts_Designer6]

00:05 Introduction to Feature Selection and Dimensionality Reduction
01:16 Understanding the benefits of Principal Component Analysis
03:22 PCA helps in sorting features in multi-dimensions.
04:16 Principal Component Analysis helps in sorting and checking quality metrics in a dataset.
06:05 Principal Component Analysis helps to separate or reduce dimensions
07:09 Identifying a point of view to separate data visually.
09:12 Explaining PCA principles
10:12 An overview of data separation using PCA.
12:40 PCA helps in visualizing data relationships.
13:51 PCA deals with differences in data distribution.
16:11 Understanding the difference between two cars based on size and shape.
17:12 Understanding PCA through crime scene analogy
18:53 Understanding Principal Component Analysis (PCA)
19:35 PCA plots help in understanding relationships among multiple variables.
21:25 PCA helps in scaling data for analysis.
22:25 PCA reduces the dimension of the data.
24:55 Understanding dimensions and paths in data
25:40 Understanding PCA and its significance in data analysis.
28:49 Principal Component Analysis helps to rotate the data for better visualization.
30:06 Introduction to PCA in machine learning
32:01 Principal Component Analysis in feature selection
33:01 Variation and covariance in PCA
36:04 Understanding Principal Component Analysis (PCA)
37:14 Principal Component Analysis finds new dimensions in data
39:30 PCA helps identify key views for differentiation
40:46 Principal Component Analysis (PCA) involves linear combination of features to generate a best fitted line.
43:24 Understanding Variance in Data
44:33 Understanding Variance in Principal Component Analysis
46:55 Principal Component Analysis aims to maximize spread in data
47:51 Understanding Covariance Matrix importance
50:58 Understanding vector directions in PCA
51:51 Understanding opposite directions in advice-giving scenarios.
53:46 Understanding vectors and their importance in AI.
57:28 Understanding eigen vectors and values in PCA
1:05:34 Introduction to Linear Algebra in PCA
1:06:50 Principal Component Analysis (PCA) deals with transforming vectors without changing direction.
1:08:28 Principal Component Analysis represents data through linear transformation
1:09:16 Understanding the importance of principal axes in PCA
1:12:02 PCA requires data scaling for accurate results

[@mhassanrazzaq1]

amazing