Full Machine Learning Project — Low-pass Filter & Principal Component Analysis (Part 5a)
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In this video, we will learn how to apply the Butterworth low-pass filter and principal component analysis (PCA) in Python.
👉🏻 Source material for this week: https://docs.datalumina.io/tjGyJjXxfp...
⏱️ Timestamps
00:00 Introduction
01:22 What is feature engineering
02:23 Python files
05:00 Loading data
07:08 Dealing with missing values
12:16 Calculating set duration
19:26 Butterworth low-pass filter
30:35 Principal component analysis (PCA)
39:42 Sum of squares features
Project overview (what you will learn)
Part 1 — Introduction, goal, quantified self, MetaMotion sensor, dataset
Part 2 — Converting raw data, reading CSV files, splitting data, cleaning
Part 3 — Visualizing data, plotting time series data
Part 4 — Outlier detection, Chauvenet’s criterion, local outlier factor
Part 5 — Feature engineering, frequency, low pass filter, PCA, clustering
Part 6 — Predictive modelling, Naive Bayes, SVMs, random forest, neural network
Part 7 — Counting repetitions, creating a custom algorithm
Link to playlist: • Full Machine Learning Project: Coding...
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