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Developing Bots. Primers - Workshop Lublin!

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Lublin

Wojciechowska 7E

20-704 Lublin

Poland

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Developing Bots. Primers

During the workshop, we implement three different types of bots. We have prepared few notebook 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 a Slack, Telegram and Messenger bots.

In the beginning of day one of the course 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 are working.

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 use some methods to deal with to recognize a context and manage 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.

Target Audience

  1. Data scientists who have little or no experience with bots, natural language processing, or natural language understanding.

  2. Python developers who would like to extend their knowledge of bots for practical usage.

  3. Any developer who has at least some basic knowledge of Python and would like to extend their knowledge of Python for machine learning.

Prerequisites

  • Basic Python knowledge,

  • Recommended: basic machine learning knowledge

Expected Outcomes

  1. Participants will understand…

    • how to use NLP methods,

    • how machine learning methods are used for bots,

    • generative and relative approaches to NLU,

    • how use sentiment analysis.

  2. Participants will be able to…

    • develop their own bot using common tools like NLTK, spaCy, Cortana and Alexa to develop their own bots

    • build machine learning models using common solutions in Python,

    • Is there a third bullet we can add here, for what learners will be able to DO after taking the course?

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 a 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 - 45 min.
  • 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 - 90 min. Seven exercises
  • 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 - 120 min. Two exercises
  • Tensorflow elements explanation

  • Build a linear regression model

  • Build a random forest classifier

  • Different types of neural network architectures

  • Build a recurrent neural network fo

Natural Language Understanding - 120 min. Three exercises
  • 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 - 120 min. Two exercises
  • 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 - 90 min. Two exercises
  • 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 - 120 min. Two exercises
  • Different approaches to text generation

  • Text generation with a simple recurrent neural network

  • Introduction to generative models

  • Build a VGAN for answer generation

Summary and final notes
  • Go through available other bots solutions like chatfuel


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


OPTIONAL

Speech Recognition - 45 min. Two exercises
  • Text to speech usage examples

  • Configuration of AVS API

  • Build a sample Alexa HR pipeline skill


Duration

2-days workshop

We provide a delicious complimentary meal, coffee and snacks.

If you have any further questions please contact us via olga.sroka@codete.com

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Lublin

Wojciechowska 7E

20-704 Lublin

Poland

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