AWS ML - Part 2

2.2 Perform feature engineering.

 Identify and extract features from data sets, including from data sources such as text, speech,

image, public datasets, etc.

 Analyze/evaluate feature engineering concepts (binning, tokenization, outliers, synthetic

features, 1 hot encoding, reducing dimensionality of data)

2.3 Analyze and visualize data for machine learning.

 Graphing (scatter plot, time series, histogram, box plot)

 Interpreting descriptive statistics (correlation, summary statistics, p value)

 Clustering (hierarchical, diagnosing, elbow plot, cluster size)