Data science and Machine learning regimes: a curiosity driven attempt
Sometimes, I do certain things merely for the simple reason of curiosity. It is NOT a declaration of my expertise per se, by any means. As a matter of choice, it is an effort that I put in just to know-how (at least I acquired a basic understanding of Data Science&Machine Learning). If learning is a continuous process, any self-proclamation or certificate can not define expertise in any respective field. Although, it is a noble thing to start your journey.
I am a trained computational plasma physicist and currently working as High-Performance-Computing user support at CINECA, Italy, where we have tackled all sorts of computational challenges. The pinnacle of my excitement in this field is learning things and executing them, which sometimes can be painfully enjoyable. But this goes for every outcome.
So, what drove me into this field? Surely, it is the buzz of Data Science, Machine learning, and AI, and lack of my knowledge in this field. Just like a system needs upgrading after a while, so do our skills. I was interested not because I was hunting for a possible career path, but to upgrade my skills, regardless. It goes beyond learning technology. I recently developed a basic understanding of economics, history, etc.
This is the way I carved my path into the field of Machine learning and Data Science. I would not dare to advise anyone to follow, have your experience and do your due diligence.
- Getting your fundamentals in order: There is no other way. Python seems to be a preferable language. Although, I was familiar with writing code in Python. I decided to take a cohesive course. Teaching is an art. One could acquire so much knowledge, but passing it to others is a unique skill. I found the Zero to Mastery Machine Learning course, taught by Andrei Neagoie, certainly, is the best course on Udemy. There is no surprise that Andrei is rated number 1 Udemy instructor.
His holistic teaching approach helps you follow the course thoroughly. Even if you know Python, there is no harm in taking this course. Apart from learning the basics of Python and Machine Learning (at least the gist of it), you will learn how to think like a programmer.
2. Accolade a detailed course of Machine learning: My quest for knowing more about the hack of Machine Learning was not stopped there. Wanting to know more about it, I subscribed to another course on Udemy about Machine Learning A-Z!. Oh boy, this was quite a long course. Because of this reason, I decided to follow the Python version of code implementation. The course will provide everything that you need to know about Machine Learning. Both instructors, H. Ponteves and K. Eremenko made a tremendous effort explaining the topics, especially Ponteves. You will get all well-structured code implementation in Python and R. The course will guide you in detail on code implementation of Data Preprocessing, Regression methods, Classifications, Clustering, Reinforcement learning, Natural language processing, and Deep learning. The last one is the one I enjoyed the most. Comparing the results from each of these methods was also very insightful.
Those 80 hours were well spent.
Where I go from here: Many people on the internet have recommended that one should take a course on Deep Learning Specialization (by Andrew Ng) which I have yet to attempt.
And of course, this is not enough. Real success would be to find a problem and apply this knowledge in search of finding a solution on my own.
It goes without saying that to achieve anything, you need commitment, persistence, and patience.
PS: These are my personal experiences. In the manner that I learned from others, I follow the same path to share my experience. So please have your experience and share it with others. “Knowledge, in contrast, is a growing resource — the more you use, the more you have- Yuval Noah Harari ( @Homo-deus-A brief history of tomorrow). It is often said for getting a successful attempt there are several hurdles, for one good relationship, there are several failed relationships. In the end, you will get there, just keep moving forward. Being a bully is not a human virtue. Please be KIND to others.
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Nitin Shukla,
13th February 2021, Bologna Italy.
SuperComputing Applications and Innovation Department
CINECA — via Magnanelli 6/3, 40033 Casalecchio di Reno (Bologna) — Italy
hpc.cineca.it
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