Deep Learning with TensorFlow (1 or 2 days)

Deep learning is the area that wins over the field of Artificial Intelligence. By using libraries like TensorFlow, it is now available to the wider audience.

In this workshop, Barbara will walk the audience through the process of creating and training the deep neural networks on the task of image classification. The session will start with explaining fundamental concepts of machine learning and introducing the dataset the computation will be performed on.

The Workshop will cover the following areas:

  • Introduction to Machine Learning problems, process and algorithms
  • Deep Learning concepts: Neural Networks, Forward Propagation, training process
  • TensorFlow Basics: Constants, Placeholders, Variables and optimisation process.
  • Neural Network architecture and training with TensorFlow
  • Convolutional Neural Networks
  • TensorFlow abstraction levels and packages

Using the interactive learning platform, attendees will have the practical opportunity to use TensorFlow when building deep networks, training them and evaluating the results. After the session, participants will become familiar with how to use TensorFlow when shaping the architecture of neural networks.


Machine Learning with R (1 or 2 days)

Every day we are noticing that applications are becoming more intelligent. Using Machine Learning they can predict your online shopping preferences, movies you want to watch or interesting articles.  R platform is considered to be number one environment for statistics, data science and data visualisation. It offers libraries and ready to use implementations of machine learning algorithms.

In this workshop, Barbara will walk the audience through the process of implementing machine learning algorithm for classification, regression and clustering problems using R language. The tutorial covers the following topics:

  • Machine Learning process and creating predictive models
  • Introduction to supervised and unsupervised learning
  • R basics for data preparation and alterations
  • Elements of Exploratory Data Analysis
  • Resampling methods
  • Using R language when implementing regression classification and clustering algorithms
  • Methods of scoring and evaluating
  • Tuning the Machine Learning models
  • Using R for visualisation

During this workshop, attendees will get familiar with basic concepts of machine learning process. They will learn how to use R platform when preparing the data, creating predictive models, evaluating them and presenting the results.

Data Exploration with R (1 day)

R platform is considered to be the number one environment for statistics, data science and data visualisation. It has made the world of data analysis and performance much more approachable. But first of all, R offers set of tools perfect for data exploration, the preparatory phase for drawing any data science conclusions.

The workshop is based on the set of exercises introducing step by step the world of data exploration in R and covers the following topics:

  • Data structures and conversions between them
  • Loading and saving data from and to different sources/destinations
  • Working with matrices and data frames
  • Indexing and filtering data
  • Organising data: transposing tables, sorting, subsetting
  • Sampling techniques
  • Cleaning the data: handling missing values and duplicates
  • Working with frequency tables
  • Aggregate operations
  • Merging and joining datasets
  • Elements of Exploratory Data Analysis and data visualisation

During this workshop, attendees will learn how to use R when exploring their data. This could allow them to turn unstructured information into useful insights.

Machine Learning with Azure (1 or 2 days)

Modern companies do realise how making use of their data can enhance the business. But building the Data Science team requires either hiring the skilled staff or putting a lot of effort into internal education. This is the place when Azure Machine Learning Studio comes in. It offers low-cost, easy to use and managed environment. The Studio provides educational space making entering the field of Machine Learning more accessible.

The workshop is a comprehensive introduction to the various Machine Learning concepts and is covering the following topics:

  • Creating the Azure Machine Learning experiments
  • Importing data from Azure sources and working with datasets
  • Data cleaning and manipulation
  • Exploratory Data Analysis
  • Performing the training for supervised and unsupervised Machine Learning tasks
  • Tuning the Machine Learning models
  • Customising the process by using R and Python code
  • Working with Jupyter Notebooks in the Azure ML workspace
  • Publishing and consuming a Machine Learning web service for predictive analysis
  • Retraining the Machine Learning model

The workshop will walk the attendees through the Machine Learning process, how to build one in Azure ML Studio and publish the predictive experiment. With the enhancement of the R and Python code, participants will have the opportunity to customise the flow. Finally, the session will provide the ways of productionising the built solution by publishing it to Azure.

Building Chatbots with Microsoft Bot Framework and LUIS (1 day)

Chatbots are the modern way of enhancing the user experience with human-like conversation. By using a proper platform, companies can easily automate the processes of making purchases, giving advice or answering support questions. Microsoft Bot Framework and LUIS (Language Understanding Intelligent Service) offer the end to end solution for systems wanting to embed chatbots into their architecture.

In this workshop, Barbara will present the building blocks of the system based on the Bot Framework. The audience will go through the exercise of creating an application for handling messages, applying natural language processing techniques by using LUIS and hosting it on Azure. The workshop will cover the following topics:

  • System architecture using Bot Framework
  • Elements of Natural Language Processing
  • Identifying the best response based on user input
  • Integration with LUIS
  • Hosting the chatbot service on Azure
  • Integrating the conversation into applications and other messaging platforms

During the session, attendees will go through the process of building a chatbot based system. The workshop starts with shaping the conversation scenario and goes through applying the intelligence to it. Finally, the project will be integrated with one of the messaging providers and deployed to Azure Cloud.