Artificial intelligence (AI) and machine learning are increasing their presences in the business world on a seemingly daily basis. These technologies have the ability to automate repetitive tasks, identify trends in unstructured data, and even make predictions that can assist companies with critical decisions.
However, organizations can only take advantage of the technologies if they have a system to support it. For smaller companies, designing a proprietary machine learning platform may be out of reach. However, thanks to open source, that doesn’t mean they can’t create a functional solution based on their unique needs.
While using the open source approach may seem risky, particularly since you don’t have full ownership over your creation, when leveraged properly, it can actually be the ideal approach. If you are interested in building a machine learning platform, here’s how to make the most of the open source options available.
Explore Existing Offerings
When you want to use open source to craft your ideal solution, you don’t want to merely grab the first option you come across. Instead, explore each one to learn its strengths and weaknesses, allowing you to choose the best approach based on your existing systems, coding preferences, or overall goals.
Today, there are multiple open source options available, including many from leading technology companies. For example, Salesforce opened up their TransmogrifAI, the machine learning library used in the company’s Einstein AI platform, that works best with structured data. Oracle’s Graphpipe may be a better option for smartphone and IoT device-oriented machine learning models where cloud-based servers are in play. And, of course, there is also a significant amount of machine learning code available from Google.
By taking a close look at the open source options that are available, you can identify existing solutions that can help you craft your ideal platform based on your needs and goals. This can be a significant timesaver, ensuring you begin your project in the best position possible.
Embrace the Community
When you use an open source approach to creating your machine learning platform, you also gain an additional benefit beyond having access to reliable starting code; you can also leverage the community. Companies and developers on sites like GitHub are more than willing to look over your code, provide suggestions, make tweaks, or even help you find errors.
By embracing the community, businesses with small development teams can make progress more quickly, resulting in a more robust solution in a shorter timeframe. Plus, they can help your IT pros learn and grow in the machine learning development arena, allowing them to enhance their skills and knowledge along the way.
Ultimately, by leveraging open source, you can build your next machine learning platform quickly and efficiently. If you are interested in learning more about the power of open source, the professionals at The Armada Group can help. Contact us to speak with one of our knowledgeable team members today and see how our development expertise can benefit you.