Python Machine Learning – Artificial Intelligence
Example of Machine Learning with Python Artificial Intelligence
Python Machine Learning
ChatterBot
ChatterBot is a machine-learning based conversational discourse motor form in Python which makes it conceivable to produce reactions in view of accumulations of known discussions. The dialect autonomous plan of ChatterBot enables it to be prepared to talk any dialect.
How it functions
An untrained example of ChatterBot begins off with no information of how to convey. Each time a client enters an announcement, the library spares the content that they entered and the content that the announcement was in light of. As ChatterBot gets more information the quantity of reactions that it can answer and the exactness of every reaction in connection to the info articulation increment. The program chooses the nearest coordinating reaction via hunting down the nearest coordinating known articulation that matches the information, it at that point restores the in all likelihood reaction to that announcement in view of how often every reaction is issued by the general population the bot speaks with.
Preparing information
ChatterBot accompanies an information utility module that can be utilized to prepare talk bots. Right now there is three dialects, English, Spanish and Portuguese preparing information in this module. Commitments of extra preparing information or preparing information in different dialects would be incredibly refreshing.
Example of Machine Learning with Python Artificial Intelligence
user: Good morning! How are you doing?
bot: I am doing very well, thank you for asking.
user: You’re welcome.
bot: Do you like hats?
Python Machine Learning Installation
This package can be installed from PyPi by running:
1 | pip install chatterbot |
Example of Python Machine Learning
1 2 3 4 5 6 7 8 9 10 11 12 | from chatterbot import ChatBot chatbot = ChatBot( 'Ron Obvious', trainer='chatterbot.trainers.ChatterBotCorpusTrainer' ) # Train based on the english corpus chatbot.train("chatterbot.corpus.english") # Get a response to an input statement chatbot.get_response("hi, my name is open source projects") |
Learn how to use Data
1 2 3 4 5 6 7 8 | # Train based on the english corpus chatbot.train("chatterbot.corpus.english") # Train based on english greetings corpus chatbot.train("chatterbot.corpus.english.greetings") # Train based on the english conversations corpus chatbot.train("chatterbot.corpus.english.conversations") |
Python Machine Learning Project
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