5 Common Machine Learning Mistakes to Avoid for Startups

May 13, 2020

Machine learning has been all over the headlines in business technology news, and for good reason. The capacity that machine learning has to innovate your business's operations is tremendous.

Machine learning is able to look at tremendous amounts of data, perform regressions analyses, and come up with recommendations on how your company can operate more efficiently.

Many startups that are looking to realize these benefits and harness the power of artificial intelligence, however, make some common machine learning mistakes. In this article, we provide a quick list of five such errors so that you can make sure to avoid them yourself.

1. Failing to Double-Check Work

The first error that many startups make with machine learning is failing to double-check the work done before implementing the recommendation made. These business decisions can often be hard to reverse and have lasting consequences on your company's operations.

Be sure that you have double-checked your work multiple times and that the recommendation outputted from the machine learning algorithms stays constant before you consider implementing it in your operations.

2. Working with Data Gaps

The next mistake that is common with machine learning is working with data gaps. Remember that machine learning is all about working with the right amount of data. With insufficient data, the regressions and patterns drawn by the machine learning tool in question can be completely wrong.

If you have data gaps in your data warehouse, fix those by retrieving lost data or by coming up with new ways to harvest the missing data.

3. Working with Corrupted Data

Another common data issue that impacts machine learning results is corrupted data. This is when data is not missing but is simply wrong. This is particularly common when the data in question is heavily reliant on human input. The simple truth is that humans aren't as consistent as machines and are thus prone to entering erroneous data.

4. Not Using the Best Tools

There are many different machine learning tools on the market, but not all of them are appropriate for your business. If you're using the wrong tool that's not optimized for your business objective, then you could easily be wasting thousands of dollars and many hours trying to achieve a result that simply won't happen.

5. Hiring the Wrong Personnel

Last but certainly not least, one common machine learning mistake that businesses make is hiring the wrong person to manage machine learning operations. Because it is such a new industry, finding qualified people to work in machine learning is an arduous task. If you allow a poorly-fitted candidate to slip through the hiring process, you'll be kicking yourself shorty.

Avoid Machine Learning Mistakes 

The best way to avoid machine learning mistakes is to hire the wrong personnel. To help you do exactly that, we've created a tool that connects machine learning experts with startups in need.

Be sure to give our online tool a try today. The many benefits that machine is sure to implement in your business are only a few keystrokes away!