Full Machine Learning Project — Counting Repetitions (Part 7)

Want to start freelancing? Let me help: https://academy.datalumina.com/freelance Want to learn real AI Engineering? Go here: https://academy.datalumina.com/accelerator 💼 Need help with a project? Work with me: https://www.datalumina.com/ Welcome back! In this video, we are going to create a function that can count repetitions based on the accelerometer and gyroscope data. 👉🏻 Source material for this week: https://docs.datalumina.io/etR0bumOqKG751 If you're a data professional with 1+ years experience and consider freelancing, then check out Data Freelancer: https://www.datalumina.com/data-freelancer 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 @daveebbelaar