Many people remain hesitant regarding the integration of artificial intelligence and machine learning into the world. Part of this is because they confuse what artificial intelligence and machine learning actually contribute to, which is always of real-world value. One example would be adaptive translation services. With new modes of communication emerging, more and more organizations need translation services. Doing international business without the ability to communicate in a single native language creates a challenge of hit-or-miss accuracy when communicating with international partners. 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 translation tools capable of quickly and accurately converting communications across language barriers. What about outside of the business scope? Something more related to everyday use? Anticipatory autocorrect is an example that many people probably see and thank on a daily basis. Think about how many times you’ve misspelled a word, but your phone immediately corrected you. That’s machine learning in action! While it’s clear that these technologies give way to value in both personal and professional interactions, there’s still much to learn about how these technologies will help each other evolve. To learn more, check out the resource paired alongside this post for more information.
Python Programming & Its Importance In Machine Learning provided by Accelebrate, a company offering courses in Python Data Science training
