Once an operational outlier, machine learning (ML) is now an IT industry priority and a key component of everyday applications. A subset of artificial intelligence, machine learning is the ability for algorithms to solve basic problems and intelligently adjust outputs to match input data more effectively. In practice, well-built ML code can make relevant recommendations or identity specific user behavior to help apps provide increased value. Worth noting? There’s also a largely silent partner in this programming progression: Python. As machine learning initiatives advance, there is a need for solid programming supports that are able to adapt to input variety and improve output accuracy. Python offers a stable starting platform with clean, user-friendly code that empowers companies to build out key functionality without sacrificing feature or form. This is evidenced through many everyday applications such as popular social media, where python-powered intelligent content recommendations make content suggestions in real-time to users. While this is just one of the ways in which Python programming is influencing our lives, there are many more. For more information on those influences, please read on to the infographic accompanying this post.
Python Programming & Its Importance In Machine Learning provided by Accelebrate, a company offering courses in Python Data Science training
