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Machine Learning Applied -
Contextual Chatbots Coding,
Oracle JET andTensorFlow
Andrejus Baranovskis, CEO andTechnical Expert, Red Samurai Consulting
Oracle ACE Director and Oracle Developer Champion
Oracle ExpertsTeam
ADF, JET, ORACLE FUSION, ORACLE CLOUD, MACHINE LEARNING
Oracle PaaS Partner Community Award for Outstanding Java Cloud
Service Contribution 2017
Session Goal
HowTo BuildYour Own Machine Learning Chatbot
AGENDA
• Technical Architecture
• Solution WalkThrough
• Machine Learning Introduction
• Implementation Points
TECHNICAL ARCHITECTURE
Machine Learning Chatbot Context Communication Chatbot UI
Classification Chatbot messaging
Chatbot Custom application logic
Generic listener
CHATBOT CONTEXT
• Chatbot framework needs a structure in which conversational intents are
defined (this can JSON file)
• Conversational intent contains:
• tag (unique name)
• patterns (sentence patterns for neural network text classifier)
• responses (one will be used as a response)
SOLUTION WALKTHROUGH
GENTLE INTRODUCTIONTO MACHINE
LEARNING
LEARNING AND INFERENCE
Training data Feature vector Learning algorithm Model
Test data Feature vector Model Prediction
REGRESSION
Regression
algorithm
Input Output
Continuous
Continuous
Discrete
REGRESSION
w - parameter to be found usingTensorFlow
KEY PARAMETERS
• Cost Function - score for each candidate parameter, shows sum of
errors in predicting.The higher the cost, the worse the model
parameters will be
• Epoch - each step of looping through all data to update the model
parameters
• Learning rate - the size of the learning step
REGRESSION EXAMPLE
w - parameter to be found usingTensorFlow
CLASSIFICATION
f{x}
Input Output
DiscreteContinuous
Discrete
Classifier
CLASSIFICATION EXAMPLE
Linear boundary line learned from the training data - equal probability for both groups
WHYTENSORFLOW?
• TensorFlow has become the tool of choice to implement machine
learning solutions
• Developed by Google and supported by its flourishing community
• Gives a way to easily implement industry-standard code
IMPLEMENTATION POINTS
QUESTIONS
CONTACTS
• Andrejus Baranovskis
• Email: abaranovskis@redsamuraiconsulting.com
• Twitter: @andrejusb
• LinkedIn: https://www.linkedin.com/in/andrejus-baranovskis-251b392
• Web: http://redsamuraiconsulting.com
REFERENCES
• Source Code - https://github.com/abaranovskis-redsamurai/shenzhen
• Contextual Chatbot inTensorFlow - https://bit.ly/2pFbTw4
• TensorFlow Book - http://tensorflowbook.com/

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