Once I began learning machine learning, I got kind of the identical feeling after I first began studying computer science. The abundance of data I want to capture, too many things to cover, different concepts, programming languages, design patterns, databases, distributed systems, you name it.
In this text, I’ll attempt to bring an engineering perspective on how I got began with machine learning to be able to tackle a text classification problem in one in all the projects I used to be contributing to, but additionally provide you with a glimpse of which solution was used to unravel the issue.
- Why
- ML in a nutshell
- Create a roadmap
Considered one of the explanations was to fill an organization bottleneck. As an engineer that’s captivated with solving problems and startups, I feel the eagerness to continue to learn recent things and produce recent ideas to the table. On this particular case, it was a bit different. The duty in hands implied a technical problem that needed a complete redesign. As a matter of fact, the technical problem the corporate was facing was related with text classification [1]. In a nutshell, the last word goal was to…
