I got done reading the book The War of Art today (definitely a good read), and I really loved one of the last chapters called “The Territorial Orientation”, where he speaks about having personal territories.
A personal territory could be pretty much summed up through the following words:
"There's a three-legged coyote who lives up the hill from me. All the garbage cans in the neighborhood belong to him. It's his territory"
Just like how the coyote has a territory, each one of us would have our own territory. For Mark Zuckerberg, it was his dorm room. For Elon Musk, it is one of the Tesla Factories. (For me, it is the desk I have home)
One key point to remember (among the other points he mentioned in the book), is that a territory isn’t just a place that you “work” or spend your time at. A territory can only be claimed by work. To earn your territory, you should put in your efforts to do so. “A territory doesn’t give, it gives back”. Cristiano Ronaldo didn’t earn the football pitch as his territory in one night.
These are the other qualities of a territory (as mentioned by the author):
- A territory provides sustenance: A territory in itself doesn’t bring you down, or burn you out. “A runner would know what a territory is”
- A territory sustains us withought any external input: A territory doesn’t require you to nurture it, it requires you to put in effort and love; “the territory absorbs this and gives it back to us in the form of well-being”
- A territory returns exactly what you put in: They are fair. “What you deposited, you get back, dollar-for-dollar”
Do you have a territory too?
If so, "What's your territory?"
- Completed the book - The War of Art (by Steven Pressfield)
- Learnt more about Flight Clustering (through K-Means Clustering Algorithm)
- Practiced Designing Web Pages, using Figma
- Read through the documentation and tried few (clustering related) functions and classes of Sklearn
- Start reading the book - The Psychology of Money (by Morgan Housel)
- Work on the report for PS-1
- Test out clustering algorithms (especially K-Means) using more datasets online
- Continue getting familiar with Figma