sobota, 30. marzec 2019, Codete, Developing Bots. Primers - Workshop Kraków!

Z 30. marzec 2019 - 9:00
Do 31. marzec 2019 - 17:00

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Developing Bots. A Primer
During the workshop, we implement three different types of bots. We have prepared a few notebooks to be done before the course to the participants a short introduction into chatbots. We implement an HR assistant bot that can be a basis for your projects. We show how to develop Slack, Telegram and Messenger bots.
At the beginning of day on one of the courses we present bot taxonomy and machine learning terms related to bots. Next, we go through natural language processing and natural language understanding. Between both, a short introduction to tensorflow is given. It is needed for better understanding of how natural language understanding methods work.
During day two we go into more complex topics like sentiment analysis, context management and how to build intelligent bots. We show how to develop a vectorizer and build a sentiment analysis method. This method is next compared with other solutions that are available on the market. The context management is a complex topic and we show how to use some methods to deal with context recognition and management in case we have more than one. The last part is dedicated to generative models and how to build intelligent bots.
The course ends with a homework where the methods explained during the course should be used by the participants in given homework examples. Additionally, there is one optional notebook for speech recognition.

Prerequisites


Basic Python knowledge,


Recommended: basic machine learning knowledge



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Outcomes


Participants will understand…


how to use NLP methods,
how machine learning methods are used for bots,
generative and relative approaches to NLU,
how to use sentiment analysis.


Participants will be able to…


develop their own bot using common tools like NLTK, spaCy, Cortana and Alexa,
build machine learning models using common solutions in Python,
Agenda
BEFORE


Anna HR Slack bot



Slack and trello API introduction


Few examples how to deal with RTM and Events API


Setup Trello and use it to build an HR process pipeline



Greg stock market messenger bot



Messenger setup explanation


API explanation


Combine it with Alpha Vantage stock market API



Paul customer service telegram bot



Telegram API explanation


Building a simple Telegram bot




DAY 1


Introduction to bots:



Bot taxonomy


List of known bots and bot platforms


Usage examples



Machine learning and bots



Short explanation of NLP/NLU and machine learning usage for bots


Three generations of bots explanation






Natural Language Processing



Regular expressions and Python methods used for text processing


Corporas, NLTK and tokenization


Part of Speech and Tagging - examples with NLTK and Spacy


Text normalization


Lemmatization


Sentence extraction


Noun chunks


Named Entity Resolution


TFIDF and bag of words






Short introduction to Tensorflow



Tensorflow elements explanation


Build a linear regression model


Build a random forest classifier


Different types of neural network architectures


Build a recurrent neural network






Natural Language Understanding



Similarity measures


Vector Space Model explained


Type of vectorizers


Build a vectorizer with Tensorflow


Intent and entities in NLU explained


Using SpaCy language model and Rasa for intent understanding




DAY 2



Sentiment Analysis



Introduction into sentiment analysis


CoreNLP and TextRazor used for sentiment analysis


Implement a PCA Tfidf vectorizer for sentiment analysis


Build a simple sentiment analysis model






Context management



Introduction to the problem of context management


Use similarity measure to get the context of the conversation


Intents in context management


Implementation of a neural network for context recognition


Updating a model in tensorflow for continuous context learning






Intelligent bots



Different approaches to text generation


Text generation with a simple recurrent neural network


Introduction to generative models


Build a VGAN for answer generation




HOMEWORK



Anna - HR assistant bot



Build a dataset for Rasa to understand the intents to cover the full HR process pipeline


Use sentiment analysis to get the sentiment of candidate and company feedbacks






Greg - stock market advisor bot



Extract the nouns and users’ intent to manage the stock market actions






Paul - customer support bot



Use text generation models to response for customers’ questions


Introduce a neural network to get the context and build a management tool for it




Timeline
2-day workshops

We provide a delicious complimentary meal, coffee, and snacks.
If you have any further questions please contact us via

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