Full Machine Learning Project — Coding a Fitness Tracker with Python (Part 1)
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In this video series, we are going to build a fitness tracker in Python that can classify various barbell exercises based on accelerometer and gyroscope data. This will be a full machine learning project and new videos will be released weekly, so subscribe to stay tuned!
👉🏻 Source material for this week: https://docs.datalumina.io/xLAtq6PNUsMcfG
⏱️ Timestamps
00:00 Introduction
01:16 Project objective
01:58 Project background
07:46 The quantified self
10:40 Project overview (what you will learn)
17:37 Action items (complete these now)
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: https://youtube.com/playlist?list=PL-Y17yukoyy0sT2hoSQxn1TdV0J7-MX4K
If you find these videos helpful, consider subscribing at @daveebbelaar
Видео Full Machine Learning Project — Coding a Fitness Tracker with Python (Part 1) канала Dave Ebbelaar
Need help with a project? Work with me: https://www.datalumina.com/solutions
In this video series, we are going to build a fitness tracker in Python that can classify various barbell exercises based on accelerometer and gyroscope data. This will be a full machine learning project and new videos will be released weekly, so subscribe to stay tuned!
👉🏻 Source material for this week: https://docs.datalumina.io/xLAtq6PNUsMcfG
⏱️ Timestamps
00:00 Introduction
01:16 Project objective
01:58 Project background
07:46 The quantified self
10:40 Project overview (what you will learn)
17:37 Action items (complete these now)
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: https://youtube.com/playlist?list=PL-Y17yukoyy0sT2hoSQxn1TdV0J7-MX4K
If you find these videos helpful, consider subscribing at @daveebbelaar
Видео Full Machine Learning Project — Coding a Fitness Tracker with Python (Part 1) канала Dave Ebbelaar
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24 ноября 2022 г. 23:33:02
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