On comparing ourselves to others
This week I’ve noticed myself drawing comparisons between the path I’m on and the path of those I admire.
In particular, I’m very aware that the majority of my role models ‘made it’ before they became a parent.
I’m a new parent but don’t feel that I’ve ‘made it’ yet. This makes it harder for me to see myself following in their path (and I’m looking for parent role models).
At times, this can be a source of frustration, however I’ve been trying to keep the (slightly cliched) advice in mind:
Don’t compare your start to someone else’s middle
or, as Jordan Peterson puts it:
Compare yourself to who you were yesterday, not to who someone else is today.
We each have our own path, and will progress at different speeds in different domains (plus not everything is about ‘progress’). Comparing ourselves to others takes a lot of the fun out of it :)
Nothing ground-breaking this week, but I found this a helpful reminder.
Machine Learning for Healthcare video series
I’ve decided to fully digitise the ‘machine learning for healthcare’ courses that I’ve been running in London for the last year or so, and make it freely available on YouTube.
I’m going to be recording a series of around 8 or 9 videos this coming week. I’ve got a number of big commitments from then on until the end of the year, so am not sure how many more machine learning videos I’ll record, so I’m keen to include as much useful information as possible in this video series.
If you have an interest in machine learning applied to healthcare, and have any questions or topics you would like to hear answered or discussed in this series of videos, please hit ‘reply’ to this email and drop me a quick line! Chances are if you are thinking about it, someone else is too - so you will be helping anybody who watches the course in the future.
This week’s links:
I’ve been dipping in and out of this list of AI tools for design. I find the idea of AI-assisted / AI-generated art really interesting, and actually spent this week decorating my house with posters after training a neural network to perform style transfer on images with personal significance. (I’m going to be doing the same for a few friends, so drop me a message if interested!)
(2) A podcast: “Philosophize This”
I have been embracing my inner armchair philosopher, and enjoying this podcast which discusses key philosophers from throughout history. The partner, who has a degree in philosophy, advises me that it’s fairly superficial, but I’m enjoying it nonetheless :)
This week’s video:
In the last few weeks, I’ve received several offers to work as a data scientist or machine learning engineer. I put some of this down to my approach to preparing for interviews, and decided to record a video outlining the approach that I took.
In particular, I devised a ‘project based’ approach to preparing for interviews, which made the whole process a lot more enjoyable:
Enjoy this email?
Please click the heart below, and forward the email to a friend!
Hi! I’m Chris Lovejoy, a Junior Doctor and Data Scientist based in London.
I’m on a mission to improve healthcare through technology (particularly AI / machine learning), but along the way I want to share learnings that are relevant no matter your career choice or background.
In this weekly newsletter, I share my top thoughts and learnings from each week, as well as links to the best things on the internet that I come across.