Differences between Tensorflow and Dialogflow

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So I’m starting out in the world of AI and Machine Learning and let’s say that not everything is well explained to beginners (maybe my ill will? maybe). I wanted someone to explain to me the difference between Tensorflow and Dialogflow, and if they approach the same thing, what is the advantage of each one.

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I confess that I did not know Dialogflow until then, so I may not have a 100% complete answer.

But as far as I understand Dialogflow is a platform that assists in the development of applications that need NLU (Natural Language Understanding). Let’s say you want to create an app in which the user talks to the mobile phone which menu item he wants to access, in this case Dialogflow applies well. It functions as an abstraction of AI methods, being useful when you want to develop something quickly and/or in which AI is not the differential.

Tensorflow is a library focused on neural networks, which today are in most Machine Learning algorithms. You could implement everything Dialogflow offers you by Tensorflow, but you would have to do more in "hand".

If your goal is to study and learn AI, studying Tensorflow is an excellent way. If you are very beginner I recommend starting with Scikit Learn, which has the most basic Machine Learning techniques, but will allow you to have experience in the middle.

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