Data & Features
How raw data becomes meaningful signal
⬡ 4 topics · 19 chapters · ◷ ~6.2 hrs
Topics
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01
Understanding Data
What data actually is before any algorithm touches it
foundational ◷ 95 min ≡ 5 chapters
01 Datasets
02 Data Types
03 Distributions
+2 more
02
Features & Representations
Turning raw observations into numbers an algorithm can use
foundational ◷ 124 min ≡ 6 chapters
01 Feature Vectors
02 Categorical Encoding
03 Normalisation
+3 more
03
Dimensionality
What happens to data and intuitions when features multiply
intermediate ◷ 79 min ≡ 4 chapters
01 Curse of Dimensionality
02 Correlation & Redundancy
03 PCA
+1 more
04
Data Splits & Evaluation Foundations
How to know whether your model has actually learned anything
intermediate ◷ 76 min ≡ 4 chapters
01 Train / Val / Test
02 Cross-Validation
03 Overfitting & Underfitting
+1 more