It has been a year since I jumped into the AI and machine learning hype train by studying related materials online during my spare time. I am grateful that I can now apply some of the knowledge into my current research. Seeing those techniques in practice also motivates me to continue to improve my skills.
Even without all the hypes, I think the time that I spent every night trying to understand those mathematical equations and machine learning concepts taught by the likes of Andrew Ng, Laurence Moroney and IIkay Altintas have all been worthwhile.
Many fields, such as the ones that I have worked previously (semiconductor manufacturing), are not utilizing the many million data points available. These precious data are recorded and generated from the expensive inspection tools and sensors installed into the production lines.
While I was working in these fast-moving industries, there were many occasions where explaining complicated phenomenon is impossible with science, especially within a short period of time. I have since realised that it would be helpful if the team had some understanding and awareness of the available data science tools.
Perhaps there could then be more incentive and effort, for example, just to locate correlations between the many different processing conditions to find the right (correct) way to improve device performance. Or to spend more time digging deeper into the data to find and predict some useful trends to describe those hard to explain phenomena.
I also feel that learning data science skills by myself is more beneficial compared to working externally with data scientists. This is because instinctively, you have a broader understanding of the data and problem at hand. You can work on the problem right away, while also gaining new insights from the process.
Furthermore, the awareness that I gained from the deep learning courses by Andrew Ng and Laurence Moroney have been immensely useful in my last entrepreneur adventure. In particular, these knowledge gave me confidence to look for startup ideas that are related to AI.
I also become more appreciative of those statistics and linear algebra courses that I studied back in university. They have been useful to understand data science concepts, and help to explain the data in more details.
Lastly, I find that learning new things are also a way to explore our interest beyond whatever that we are doing professionally. Perhaps you may find something new that excites you. The new experience may give you enough courage to take the next leap of faith in your life. For example, spending the next few years working on something that you love and enjoy the most.
