Getting (re)Started on Machine Learning
Machine learning is a well-sought-after skill in today's job market, and I think it will continue to be in the near and medium future. Despite knowing its widespread application across many industries, I've failed to learn it in the past, just like many others. However, this time around, I'm determined to succeed and want to share my journey with you.
One primary reason why I think I failed before was my negative mindset. I believed that I wasn't cut out for it, that it was too complicated, and that I needed to be a math genius to master it. But I've learned that many data scientists felt the same way when they started, and the key is pushing past that thinking. So, I've been challenging my self-limiting beliefs and replacing them with positive and empowering thoughts, reminding myself of my past successes when I thought something was impossible.
Another reason why I struggled in the past was that I didn't use the right resources. I jumped straight into advanced materials without a good foundation in the basics. This time, I'm starting with the basics and looking for resources that assume no prior knowledge, targeting absolute beginners. Many free and paid resources are available online, and I've recently started a course (Supervised Machine Learning: Regression and Classification) on Coursera taught by Andrew Ng, which has been helpful so far in understanding complex ideas.
Lastly, what's different this time is that I have a clear goal. I want to focus on classification machine learning algorithms because of a work project requiring it. Having a focus means I'm less likely to get lost in the vast sea of online information, and I believe it will help me stay motivated.
To conclude, I'm still aware that machine learning is challenging, but I have renewed confidence and belief that I can learn it. By overcoming my challenges by challenging my beliefs, starting with the basics, choosing appropriate resources, and prioritizing learning, I'm confident I have a better shot at achieving my goal this time. If I don't succeed, I'll reflect on what went wrong again and what I could do differently next time. I want to close this blog by sharing the four lines below. I have it on my wall. It keeps me moving when I'm not feeling great and lacking motivation.