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What I learned this Week. Week 7.

Welcome back. This week was pretty uneventful. I do hope you enjoy my take on a pretty lowkey week.


Today was a great day. If you are back from last week, you know that I published and finished last weeks retrospective today. I encourage you to read it if you haven't already. I did finish my practice course from leetcode Sunday and am starting a new one today. It blows me away that just from being consistent, I have solved over 30 problems and am on a 15 day streak that I plan to continue. I am writing this a little later than normal because I had a friendly meeting with a statistician that teaches at MIT and Harvard. The meeting went wonderfully and I feel like it's a start to an amazing opportunity.


Today was good. Nothing eventful happened today. I did my morning routine without any distractions. I was able to get through my to-do list comfortably. Ran a few errands and now here I am. It's early even and I am done for the day. Well almost done, I still have to write this. Because I don't have a lot going on today I want to bring attention to the fact that that's okay. You don't have to be productive the entire day to be worthy of some R&R. I happened to fly through my work today and am taking the rest of the day for myself.


Another good day. Yet again nothing really happened today. I went through my morning routine and finished up my daily tasks. Although this week is a little different, my cousin is home alone this week and I will be bringing him to and from work. So I have a little bit less time on my hands. Today being a day for technical learning, I dove into my first topic that I wanted to learn more about: Factor analysis(FA) in python. I have some experience with principal component analysis(PCA) which is similar and a type of factor analysis. PCA components explain the maximum amount of variance while factor analysis explains the covariance in data.
I have yet to implement what I learned on my dataset, but am excited to try it out. I put the link there for anyone wanting to see what I am up to.


Today was alright, pretty boring but nothing to complain about. I have been utilizing googles job search engine to easily find lots of jobs I easily qualify for. I have been applying to 5-10 jobs every Tuesday and Thursday since last week and plan to continue this trend. Linkedin bore some fruit today as well with a recruiter coming up on my feed. He is looking to fill jobs for remote data scientists, which is exactly what I'm looking to do. I reached out and am hoping for the best. I had a few extra practice problems today which was kind of fun.


Today was great. I ended up waking up early feeling rested and was able to start my day an hour earlier. I finished up my daily practice problems and starting looking more into factor analysis. I was able to implement what I learned on my dataset I mentioned on Wednesday. And after some tuning, I was able to get my Kaiser-Meyer-Olkin test numbers above 0.6 and created a model. I ended up with 3 factors and was able to account for about 57% of the variance, up from 27% with my baseline ordinary least squares model. With this being only my first step, I am very much looking forward to the rest of my exploratory analysis.

Like I said, not a lot going on. But that doesn't mean it was a bad week. I progressed wonderfully with my know-how for exploratory data analysis. I have a new acquaintance who I hope to become friends with through our work together. And I have more opportunities every day.

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