Introducing : #TechToolboxTuesday & #TechToolboxThursday
Reading Time : 5 minutes
Day 8/30.
IT IS FRIYYAYY 🥳! And so I am going to keep this post as short as I can so you can go ahead and enjoy the rest of the weekend - but hopefully look forward to what I have planned for the next 3 weeks.
I was very excited about starting this 30-day learning & sharing challenge. As I talked about in my first post, the idea stemmed from a book I read. However, even though it has only been a week, the love and encouragement I have received on all the different kinds of posts has been so overwhelming -in a good way. I don’t want any of the posts I put out to be sub-par just because I am giving myself only a couple of hours to write each of them. And so when I wake up and decide what I am going to post that evening, there are a few thoughts that come to mind:
WHO is my audience?
WHAT level of detail is required?
Can I do justice to the post in 6 or so hours?
And then I go back-and-forth a lot about what I am going to write. Since my main goal is to share what I know, and when I am comfortable with how much I know, writing the post is not the difficult part in these early stages. The conceptualization of what I will write about is.
Last night I put up a poll on Instagram asking whether you, as readers, are more interested in posts about Data Science or Data Structures. I can’t say the results were unanimous, in fact, there was almost a 50-50 split (48-52 at the time that I started writing this post). Since that means I have an audience now for both the kind of topics, I will devise a plan to share posts from both the fields. It makes sense because a lot of my readers are either students or are staring school in the Fall, and so a thorough understanding of data structures and algorithms goes a long way (I discussed this in detail in Part 1 of my Interview Preparation Checklist). I am of the personal opinion that learning to code in the near future will be like math - each one of us should know the basics at least. Coding should be a part of the school curriculum for everyone, and given that we live in the age of internet, the amount of “data” we have access to is bewildering. So whether you’re at school or an industry professional wanting to work more with data, or whether you are not even in tech but fascinated by how there are “computer programs” that can tech themselves to learn - I think you’re right and Machine Learning of the future is going to be a tool that anyone can access.
I am not even going to think that my knowledge can compare to the giants who have written amazing books on all of these topics. This blog and any of the posts here cannot give you the knowledge that those very books can. However, if there is one thing I know I can help you with is developing an intuition. Until May 2018, I was working in a Biology lab, performing experiments on moths and mice, collecting data to help me understand various aspects of their motor nervous systems. Flash-forward two years, I have now completed an Applied Science Internship at Microsoft, having worked on a Deep Learning Project for them and will be starting a Software Engineering internship for another company in a month’s time. Over the 22 or so years that I have been a student, I think I have developed a skill for learning by not cramming / rote-learning concepts, but by understanding them and building an intuition around them. That, in my opinion, has been one of the most important things that has helped me be successful in the “tech-industry” as a new comer. And that is why I will never claim that my blog posts should be your one-stop to learn a new topic , but I will try to make them as useful a resource as possible so that they can help you retain the information. I want to write about how I learn, my final understanding of these topics, tell you the resources that I found useful & how I used them. There will be some topics that I will write about without the Math involved, just because the application of the algorithm is more important in my opinion. In other topics, I will go into detail of the math so that the future topics you study whether on this blog or not, become much easier. So here’s what I am thinking :
Monday : I go into the details of all the steps I discussed in my Software Engineer Interview checklist, one by one.
Tuesday : I talk about my understanding of one data structure / algorithm
Wednesday : I walk through a leetcode problem based on the data structure / algorithm discussed on Tuesday
Thursday : I discuss my intuition behind a Machine Learning / Deep Learning concept, if I have a story about a time when I was stuck and how I solved it
Friday : Too many tech days in a row - we keep Fridays a little chill. My current read, productivity tool or a rant about a product - something for everyone
Saturday : I have maintained it again and again that I want to be authentic self on this website and talk about how I have reached where I have in the hope that some of you on the same path can learn from my mistakes, and also from things that worked for me. My experience as a PhD student, transition to tech industry, being an international student in the United States - all of them are fair game.
Sunday : On Sundays we get ready for the new week - a dose of weekly motivation for you and me, both.
So here is my request to all of you, we will have ~3 posts on each of the topics above in the remaining 30 Days of Sharing Series. Too many algorithms, not enough weeks. Please let me know in the comments below if there is something in particular you would like me to write about, whether in data structures or in data science, as well as LeetCode questions - I will prioritize that. The same holds true for the questions that you have about me and my journey, I have some things in mind that I would like to talk about but if I get more questions here, I will take them up first.
Have a great weekend ahead!
