Janani Ravi | Duration: 16h | Video: H264 1280x720 | Audio: AAC 44,1 kHz 2ch | 2,76 GB | Language: English
Feature eeering is the process of using domain knowledge and insight into data to define features that enable machine learning algorithms to work successfully.
Feature eeering is a fundamental part of the data preparation workflow for machine learning solutions.
What you will learn
Qualities of effective features and how to assess them
Numeric techniques (quantization binning, binarization, transforms, scaling, normalization)
Text techniques (bag-of-x, filtering, n-grams, phrase detection)
Categorical data techniques (one-hot encoding, hashing, bin counting, etc)
Dimensionality reduction (PCA)
Nonlinear featurization (K-means clustering model stacking)
Image processing techniques (feature extraction)
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