10 Platforms for Getting Started with Machine Learning

Most recommended development and deployment platforms for machine learning projects

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Are you getting started with Machine Learning? Or, at least, planning to? If so, you’re about to join thousands of software development and data science teams that are applying Machine Learning in their projects and taking advantages of the benefits that this AI discipline offers for creating smart apps.

According to the Harvard Business Review, over the next five to 10 years, “business gains will likely stem from getting the right information to the right people at the right time”. That means that companies will build upon ML solutions to turbocharge and automate their methods of finding patterns to identify what’s most valuable to their customers. There’s a forecasted demand for Machine Learning among all kinds of industries. That’s why we’re pretty sure that it’s time for you to start preparing your team to benefit from it as well.

In order to plan how to train you to learn and evolve itself, an important step is to define which development and deployment platform for Machine Learning you’ll use. As reported by Gartner, a good ML development platform should:

  • Offer building blocks for creating a solution to a data science problem;
  • Provide experts with an environment where they can incorporate the solutions into products and business processes;
  • Grant support for carrying out data and analytics tasks;
  • Allow data scientists and developers to take tasks that encompass visualization, interactive exploration, deployment, performance engineering, data preparation, and data access.

Having these requirements in mind and based on our own experience developing ML applications, we wrote an article about 10 interesting platforms for developing and deploying smart apps. Visit the previous link and keep reading!

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