Monday May 28th, 2021: I started my second round of the 66 Days of Data challenge. I was mostly trying to organize myself and get a log for all my activities. I am trying to keep a schedule and enter all my activities for each half hour so that I can guarantee that keep a good work-life balance since things do tend to get hectic. Hopefully, I will not get lazy and drop all record keeping. But here’s to a good start.
Firstly, I will include my weekend project. I am trying to build a Alexa-like personal voice assistant. I know could never be as optimal as Alexa but I like building things from scratch like that so they can be modified however I like. I will keep this to a weekend project because it is fairly light weight and just a little too fun and unnecessary to count it during the more serious work goals I have.
Note: I should make achievable goals this round.
Second, my job hunt is still going I try to send out a few applications everyday and my strategies are to contact each company directly to get at least a conversation out of them. I am sure that if I get a quality conversation with some that will increase their confidence in me. I am working without a degree which understandably has some of them ignoring my CV….not that they are right in doing so….but I need to try different tactics.
Third, I went back into some of my project on GitHub. I want to refactor a ML project and get a better prediction. I know that I have learned a lot in the meantime so I want to apply some of these concepts. Always important to go back to old work and revise. I am afraid that I have lost touch with some ML nitty-gritty details.
Lastly, I had a good conversation with some one in the 66days community…Someone who is self-teaching like myself but needs a little focus and clarity. It can get hard at times and we need to support each other to do good work and get more out of ourselves. It was very nice to be able to demonstrate that I have learned enough to help someone out like that.
Goals for the following days:
- Get over the hump of preprocessing.
- Train a model.
- Create at least one visualization a day.