I am a data science enthusiast. I believe the most effective things in this world are simple. I like to teach complex machine learning algorithms in a simple way. I have a huge interest in IoT with machine learning. I like to do meditation.
I write about machine learning algorithms. I learn new concepts, implement them and try to present them in an easy and practical way. I try to provide the cutting edge research in artificial intelligence through my blog posts. You will get everything from basic to advanced machine learning research.
I believe data will drive the major chunk of future development. The potential that machine learning algorithms have and the way they are being used – from averting accidents in manufacturing to autonomous cars – excites me to imagine the bright future of data science experts.
I wanted to do something big and interesting in my life. As with everyone else, I also got excited with the term ‘artificial intelligence’. One day my cousin asked me to do a data science course as it offers good salary in the information technology industry. When I learned that, data science is another name for artificial intelligence, I got very excited to learn it.
I searched for the best available courses on the internet. I found one and got enrolled in it.
In the meanwhile, I learned about the basic math stuff – statistics, linear algebra and calculus.
I started the course and mesmerized by the predictive aspect of machine learning algorithms.
After learning for a while, I faced some resistance from my mind as the topics required me to do extensive brain storming, research and visualization of the functioning of the algorithms virtually ,i.e., in my mind.
I was supposed to do the assignments after each algorithm. The assignments were quite challenging.
Somehow, I managed to complete the assignments. I was still not confident that I can crack any data science interviews.
So, I started working on self projects. I did some simple projects in almost every sphere of machine learning (computer vision, NLP, deep learning, classical machine learning, etc.).
After doing the projects, I was a little confident that I could crack the interviews. As I applied for the jobs, I got some questions to solve before the actual interview.
Although I was not able to solve the problems in the stipulated time, I realized that what I have learned in the course has created a strong base.
I was able to understand all the problem and give the basic solution. Now, I just wanted to learn some cutting edge research to crack those questions.
I learned a lot at that time.
Finally, after a few days, I got a call for interview and I got selected.