This is me documenting my progress as a programmer. I foresee much excitement, much frustration and much cats. Always, cats.
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Hello HTML, my new friend
It's been awhile since I've blogged. I've been inspired to start it up again by listening to the Codenewbie podcast. I suppose it's a good way for me to keep track of my progress, or lack thereof. After monthsyears of searching for something new to learn, I've finally given in and started playing around with coding. I purchased a full stack web development course on Zenva several months ago and tried teaching myself. It was a real struggle. It took me a long time to get through the classes. At times, even after much googling, I wasn't sure what I was doing. So, I finally decided to take the plunge and join a bootcamp. It's been great so far. It feels really good to learn something new and challenging after so many years of just riding planet earth and drifting through space. I do worry that my investment will not bear fruit, but I suppose that it is up to me to make sure that doesn't happen. The struggle with imposter syndrome is all too real.
This is not my cat. I found it on the internet.
It's definitely been a bit since I've seen this graphy. Anyone who has learnt about standard deviation knows this graph. Standard Deviation Standard deviation shows us how spread out all the values in a set are from the mean. The higher the standard deviation, the more spread out the values are over a wider range and the flatter this curve. In a normal distribution, most values are within 1 standard deviation from the mean(the green part of the graph). Apparently NumPy can calculate standard deviation too! import numpy numSet = [ *lots of numbers* ] numSetStdDev = numpy.std(numSet) Variance The variance also indicates how spread out the values in a set are. It measures the average degree to which each value differs from the mean. variance = standard deviation ^2 import numpy numSet = [ *lots of numbers * ] numSetVar = numpy.var(numSet) Source: https://www.w3schools.com/python/python_ml_standard_deviation.asp
I've started on my Python course. So far, the code has been familiar because the first few basic codes are similar to Javascript. And then modules happened. Confusion and despair! What is the world is 'if __name__ == "__main__": ' and why must I reach this section of my course on a public holiday when none of the instructors are in :( Stack overflow to the rescue, providing me a lifeline while I was drowning in a pit of serpents. I feel eternally indebted to a particular Mr Fooz. Picture from here From my understanding, when the Python interpreter reads a source file, it first sets the variable __name__ and then it executes all the code in the file. If that particular file that you are running(i.e. your module) is the main program, the interpreter will assign '__name__ = "__main__" '. Thereafter, any code in the aforementioned 'if' statement is run. If you have, instead, imported a module, the interpreter assigns '__name__ ...
I was today years old when I found out what fizzbuzz was. Yes, I'm late to the party. I was in an interview where the interviewer mentioned that ordinarily they would ask interviewees in for a round of fizzbuzz challenges, as I know. Actually sir, no, I don't know 👀 But he sounded so certain that I must surely know what it is that I was afraid to say anything so I did what I always do when I panic. Look right back saying not a word. I googled this mysterious fizzbuzz problem: It looks pretty easy. I don't think he meant this actual problem, but problems like this. Because this problem is way too easy to be an actual problem someone asks in an interview. I decided to work on it for fun: Yup. Super easy. I wish this is all I were asked in an interview 😄
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