!date
still going.
still trucking in the newest year of them all.
Two Thousand and Twenty Two.
Tuesdays and Thursdays the library is open until 8:30 around here. I did my workout right away after work and it was 6:30 and I was stoked because that meant I had two whole hours to study (yeah who DOESN'T get excited about this right??? okay settle down over there).
Except it took me until about 7 to start and although I worked completely undistracted (meaning no one texted me), I did only about half an hour of studying on my six sigma greenbelt stuff. And I didn't get very far with it, maybe a page or two of notes. But this is the longest I've studied so far.
I think I could have gone longer but I forgot to hydrate after my workout and bring my water bottle. I was definitely feeling pretty woozy at the library and started losing focus/curiosity/direction for anything that wasn't water at the particular time so I figured, not passing out at the library was a good reason to cut the study session.
I'm not trying to think too much about if I'm taking good notes, whether I should be reading the textbook or watching videos. At the moment, the main pain point is putting my behind in a chair for a duration of time set aside specifically for studying the material, take some sort of record while it's happening and then stop. And try to do that everyday.
And since yesterday I've had the itch to write some code. I've just been thinking about it. I even brought my "Math for Programmers" book to the library but then I got home and I realized that there were like 5 whole machine learning books I have barely opened so I cracked one open and did the introductory coding exercise and here it is, my (copied from a book) first program of 2022:
import tensorflow as tf
import numpy as np
from tensorflow.keras import Sequential
from tensorflow.keras.layers import Dense
model = Sequential([Dense(units=1, input_shape=[1])])
model.compile(optimizer='sgd', loss='mean_squared_error')
xs = np.array([-1.0, 0.0, 1.0, 2.0, 3.0, 4.0], dtype=float)
ys = np.array([-3.0, -1.0, 1.0, 3.0, 5.0, 7.0], dtype=float)
model.fit(xs, ys, epochs=500)
print(model.predict([10.0]))I didn't run it in here because it's not super important how this works or what this does (it predicts outputs for the equation, 2X-1 and after 500 times of guessing, it predicts that 10 for X, will output 18.97something but the program's output is literally 500 lines long, gotta save your scroll strength for insta, I know, I'm so considerate). Also, what else is not important to know is that I did it after watching David Goggins rant on Instagram for a minute how you should do your best work on your hardest days because that will make it easy as pie on normal days and that was compelling enough.
What's important is that I did it.
Look at me out here giving myself credit. On my own blog. Get at me.
It's really not much. But I had a overall pretty good day, got a bunch of other wins and in a celebration of self, I'll list them here -
That's it.
Hope you have a great weekend.
Thanks for reading.