"Eat like a bird, and poop like an elephant."
I bought the Apple Watch Ultra 2.
To be exact, I have decided to keep the ultra 2 after 14 days of the “free trial” period is over.
It was almost a slam dunk or no-brainer. There were primarily two hurdles I was concerned about. The weight(size), and the price.
This holiday I got another tech toy – an M1 powered MacBook Pro 13”. One of the reasons to justify my buying decision is I will be able to “produce” more tennis tracking videos using the Mac version of the SwingVision. In this post, I’d like to share my initial review of it, after using it for a couple of sessions.
In a normal situation, I would wait for a few more weeks to get a bit more hands-on experience. Unfortunately, the city I live in imposed a new lock-down measure, essentially blocking any indoor tennis over the winter. The plan is to keep updating this with more information available.
This blog post is aiming to provide a step-by-step guide to perform advanced analytics on swimming data, captured by Apple watch. Microsoft PowerBI and Python on Jupyter Notebook are the primary tools to prepare, analyze and visualize the data.
You will learn how to export the workout data efficiently to your PC, make necessary data transformation, and understand what metrics and dimensions are available. Then I will walk you thru how to analyze the data to answer typical questions related to why certain behaviors happened. You will then see my preliminary attempt to use advanced analytics tools to predict future swimming performance.
Most importantly, you will find quite a few reference articles related to this topic, hopefully fulfilling your intellectual curiosity.
It is also the #3 articles of a series, the previous articles can be found here:
#1: How to use Apple Watch to monitor and improve swim performance
#2: Improving swimming performance with Apple Watch(WatchOS 4)