When considering the machine learning applications delivering real-world value, particularly those that are Python-powered, there are a few providing immense value. One example would be adaptive translation services. As online interactions shift away from traditional desktops to mobile devices, new modes of communication are emerging. Text messaging has now taken top spot over older methods such as phone conversations or emails, but it comes with the challenge of hit-or-miss accuracy when users hurriedly type a message to friends or family. It’s one thing to translate words or phrases into another language — it’s something else for these translations to go beyond basic conversion and include critical context. By combining the power of translation services with the adaptability of python programming, it is now possible to create text-to-speech tools capable of quickly and accurately converting communications across language barriers. Within that same vein, the way in which people communicate through text has also seen improvement as a result of Python oriented programming. Predictive communications are capable of analyzing current text and suggesting potential next steps have emerged. Anticipatory autocorrect is an example that many people probably see and thank on a daily basis. Though it’s clear that these types of advancements are clearly making a world of difference, there’s many more ways in which machine learning is improving our everyday lives. Interested in learning more about machine learning? Be sure to spend some time reviewing the resource included alongside this post.
Python Programming & Its Importance In Machine Learning provided by Accelebrate, a company offering courses in Python Data Science training
