Learn how to apply principal component analysis.
- [Instructor] Singular Value Decomposition…is a linear algebra method that you use…to decompose a matrix into three resultant matrices.…You do this in order to reduce…information redundancy and noise.…SVD is most commonly used for principle component analysis,…and that's the machine learning method…we're going to discuss in this section.…But first let me give you a brief refresher,…if you've taken linear algebra, on how SVD works.…You can see here we've got our original matrix.…This is our original data set, it's called A, and we…decompose it into three resultant matrices, U, S and V.…
U is the left orthogonal matrix, and it holds…all of the important non-information-redundant information…about the observations in the original data set.…V is the right orthogonal matrix, and it holds…all of the important non-redundant information…on features in the original data set.…S, this is the diagonal matrix, and it contains…all of the information about the decomposition processes…that were performed during the compression.…
AuthorLillian Pierson, P.E.
- Getting started with Jupyter Notebooks
- Visualizing data: basic charts, time series, and statistical plots
- Preparing for analysis: treating missing values and data transformation
- Data analysis basics: arithmetic, summary statistics, and correlation analysis
- Outlier analysis: univariate, multivariate, and linear projection methods
- Introduction to machine learning
- Basic machine learning methods: linear and logistic regression, Naïve Bayes
- Reducing dataset dimensionality with PCA
- Clustering and classification: k-means, hierarchical, and k-NN
- Simulating a social network with NetworkX
- Creating Plot.ly charts
- Scraping the web with Beautiful Soup
Skill Level Beginner
1. Data Munging Basics
2. Data Visualization Basics
3. Basic Math and Statistics
4. Dimensionality Reduction
Explanatory factor analysis6m 39s
5. Outlier Analysis
6. Cluster Analysis
7. Network Analysis with NetworkX
8. Basic Algorithmic Learning
9. Web-based Data Visualizations with Plotly
10. Web Scraping with Beautiful Soup
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