Newly Found Resources

I’ve been at my internship for almost two weeks now, but before I talk about what I’ve learned there, I’ll mention a few things I found and did before it.

First of all, I wanted to start learning C++ because it might come in handy, so I asked people for suggestions on where to do so, which led me to this awesome site called SoloLearn. They have several different programming language courses that are awesome and really easy to follow. I have since completed their Python course and paused on learning C++ in favor of doing other things. They also have a bunch of phone apps so you can learn on the go! (At least they do for Androids; not sure about iPhones.)

Another thing I found is Big Data University from IBM. They have a bunch of courses and course sequences related to Data Science, Big Data, R, Hadoop, Spark, and lots of other relevant things. I finished a few intro Data Science classes before work started, and hopefully I’ll have time to go through a few more before the summer is over. The only gripe I have about these classes is that the ones I have joined don’t let you speed up the videos and the instructors speak really slowly, but otherwise they’re great!

Also, if anyone is interested, I have been studying for the GRE (test to get into graduate schools) on an app called Prep4GRE and it’s pretty good. I like that whenever I study the flashcards or go through problems, it apparently doesn’t need an internet connection because I guess it loaded things ahead of time? That means I can study on my commute through tunnels and subways and stuff! Efficiency!

Now about my job. It’s been pretty interesting; I’ll be working partly on some NLP stuff and partly on some machine learning stuff, which is entirely great. I have already learned several things:

  1. TutorialsPoint is absolutely amazing. I have learned about PL/SQL, Spring, and RESTful Web Services from there already, and I will definitely continue going to them in the future! The tutorials are very easy to follow and provide a lot of examples.
  2. I also finished about a quarter of this awesome tutorial on Flask for Python, and it’s been very interesting. I have a tiny bit of prior experience with Django, so it was interesting to see the differences. I think Flask may come in handy next semester.
  3. In brushing up on some of my machine learning knowledge, I went through this explanation of kd-Trees and priority queues for approximate K-Nearest Neighbors classification. I also learned a bit about Random Forests and Gradient Boosted Regression Trees, but I’m not very well versed on them yet.

I am going to try to write blog posts more often so that maybe that motivates me to do and learn more things outside work.

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