Hey there 👋 Hope you are doing well 😊
We all know that this is the decade of artificial intelligence, data science, machine learning and stuff. These skills are very important and when added in resume, they can make your resume stand out of crowd. But while learning these skills it is very important to follow the right path. Misleading paths can waste a lot of your time. In this post I'll tell what mistakes I have made while I was learning ML. This post is helpful for those who are just starting their journey in AI. This will save a lot of time of yours😌
So let's get started 🔥
Didn't do much research
When I was starting my ML journey I didn't dedicate my time in doing research and collecting resources. I just jumped into it and found myself puzzled. There were times when my basics were not clear and I was so much overwhelmed by the intermediate things. And often I found myself scratching my head over different concepts. After all this I have realized that it is very important to do research before starting anything.
Directly jumped into ML algorithms
Now you know that I have not done enough research and I was so excited to study about ML that I didn't bother about learning basics and I started learning ML algorithms from day1 and seriously it was such an awful mistake that I have made. I should have started from Python followed by Math's then EDA, Feature Engineering and then ML algorithms.
Following more than one playlist/course at a time
I was studying from YouTube and I started from a playlist. At starting everything was going pretty well but later I found myself distracted from my ongoing course and started learning from numerous courses out there. I have seen different videos for a single topic and this took a lot of time. Also I was so attracted by the content, it is like whenever I found a video from MIT or Stanford I start learning from them and I was beginner back then so watching them were like committing a sin. So it is very important to stay on a playlist that you are following or are going to follow in future.
Everybody has their own way of getting things done
So this is like one of the most important things that I have understood lately. When we learn anything we do it in our own way whether it is web development, data structures or anything. When I was learning ML I used to follow different people and their techniques. When someone used Label Encoder I started using that when someone used Ordinal Encoder I started using that and this made me feel like I was drowning in an ocean. But with time I have realized that people have their own way of doing things and I have to find my own way too.
Not practicing and revising concepts
Back then I was lazy enough to implement and revise the concepts that I have learn on a particular day. And when enough time was passed it felt like a heavy baggage. I started forgetting things and found myself stuck. so it is very important to regularly revise and practice concepts.
Sticking for hours
Whenever I didn't get any concept I kept on studying it for hours and even days and this took a lot of my time. Sticking to things and completing them is very important but sticking to it for a long time and still nothing is working out is a grave mistake. If you don't get anything give it sometime or seek help from somebody else this will save a lot of your time.
Leave your damn ego
So yes I was someone who liked to get things done on my own and this is why I don't like seeking help from others. Whenever I stuck somewhere I never asked someone to help me out and this took a lot of my time. So don't repeat this mistake and ask for help whenever needed.
So these was my mistakes that I have made during my journey of ML. I mentioned them in post because I don't want someone to repeat these mistakes at the cost of their time.
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Thankyou 💚
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