As a data scientist, artificial intelligence or machine learning engineer, you should know when to draw the line between using tools you have a soft spot for and tools that actually get the work done easily and faster.
In the end that was the choice you made, and it doesn’t matter how hard it was to make it. It matters that you did.
― Cassandra Clare
As people who constantly write code, we develop soft spots for certain tools and technologies that we tend to use all the time even if they are not the best or advisable tools to use in certain instances. It is then our responsibility to know when to draw the line between using the right and appropriate tool, technology, or method, and using tools we just like.
When To Know What to Use
For any project you take as a data scientist, AI or ML engineer, be sure to know what solution the problem requires you to build. If you understand the problem statement well enough, you will find it relatively easier to build and implement your solution. In building your data science, AI or ML solution, be sure to take it one step at a time. Building solutions using a systematic or step by step approach is very essential if you aim at building solutions that can stand the test of time. Be sure to follow the ethical and generally accepted workflow of a data science or ML project. At every stage in the workflow, do a research or case study on the possible ways to tackle the problem at hand and look up the tools and technologies available for you to use. When these things are done, weigh the pros and cons that come with using each of the available tools or technologies and by your own discretion, choose the ones that will help you achieve your goals in a much easier and faster way. If there are many available options to choose from, it will then boil down to choosing anyone with a good community and content built around it to help and guide you as you use that tool or technology so as you can effectively utilize the tool or technology.
Choices are abundant, it is the right decision which is the rare one!
― Mehmet Murat ildan
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