I am very pleased to have been selected as a featured speaker at Microsoft brand-new, and already sold-out (!) conference, Ignite, taking place in Chicago, USA, this year. I started my speaking career at a TechEd in Nice in 1998, and I have learned everything about public speaking from the years that followed. I have even managed to get awarded the “Best session overall” 6 times, so I suppose this experience was useful. Needless to say, I am looking forward to Microsoft newest conference, which replaces TechEd, SharePoint and several smaller events. I will be covering Machine Learning, and I have two things to offer:

• Data Science with Microsoft Azure Machine Learning, Microsoft SQL Server and R: 1-hour 15-min session on Monday May 4 at 3:15pm
• Advanced Analytics with Microsoft Azure Machine Learning, SQL, and R: full-day, intensive pre-conference seminar on Sunday May 3 

If you are considering attending the pre-con, the abstract on the conference site is not very detailed (limited to just a few lines). Here is the full agenda, but bear in mind, I reserve the right to make last-minute changes to align it with anything that Microsoft may still announce. And if you cannot attend it, or you are looking for a more hands-on, in-depth course, consider attending my Azure ML classroom training in Stockholm on May 25.

Pre-con Seminar Agenda on May 3 at Ignite 2015

Data mining and machine learning are having their renaissance: after more than 40 years of academic research those powerful, algorithmic techniques are finally within the reach of anyone who can understand data. They are fast, inexpensive and, best of all, they find patterns and they can generate insight that business people are asking for! Rafal Lukawiecki will share his decade of hands-on data mining experience during this intensive, full-day seminar as he teaches you about the newest, cloud-based Microsoft analytical toolkit: Azure Machine Learning (Azure ML) and its very useful on-prem companion, the SQL Server Data Mining engine contained in SSAS, supplemented with gentle “I am really not a statistician” use of the open source R software, including RStudio and the Revolution Analytics engine. While you might catch a glimpse of Excel this day will not focus on it, as we will spend 90% of our time in SSDT, SSMS, R, and, of course, in ML Studio. However, before we can have fun exploring patterns and making predictions, you must understand how a somewhat unusual (for a relational guy or a girl) form of data preparation leads to finding interesting, potentially great predictive results. We will cover:

1. Introduction to predictive analytics, data mining, machine learning, and rudimentary descriptive statistics, as well as data and content types used in the process (this will be at level 200)
2. Data preparation, model building, and its very important validation, on-premise, using SQL Server Data Mining (briefly, at level 250) and in the cloud, using Azure ML (in detail and slowly, at level 250)
3. Use and model deployment on-premise (using T-SQL and DMX) and in the cloud-based (using REST web services API and some Python) at level 300
4. Overview of all the classes of machine learning algorithms, focusing on classifiers, but including clustering, regressions, and recommenders at level 300

We will also have a brief, level 400, look at balancing model performance to user requirements by selecting the correct precision vs recall prediction thresholds.  

At the end of the day you will have learned the entire process of machine learning and data mining, focusing on the often missed out part of correct data preparation, which should enable you to start experimenting with your own data straight away. Although we cannot promise that, we will also do our best to make sure you are tired, as this will be a very intensive day, so please sign up if you like the idea of learning lots in a short span of time.