22-25 April 2026 
SQLBits 2020
Art of Feature Engineering- For Machine Learning
The most challenging area of machine learning are Data acquisition, Feature extraction, Feature Selection. Almost in all data science project, 80% of time people spend in Data acquisition and Feature engineering.
There is no silver bullet to work on feature engineering. This is one of the most demanding area when it comes to any Data science project. Feature engineering is an art, it is not important which tool you use ( Python ,R, SQL, Excel) , here the more creative you are and you can act as a detective to find what is there in side the data. In this session we will discuss various techniques of Feature engineering techniques, we will discuss about the whole ML project life cycle too. If you are new to ML world , you have question like what is the difference between ML and AI. Where to start my ML carrier . This session will help you to clarify all of your naive questions.
Speakers
Sandip Pani's previous sessions
Art of Feature Engineering- For Machine Learning
The most challenging area of machine learning are Data acquisition, Feature extraction, Feature Selection. Almost in all data science project, 80% of time people spend in Data acquisition and Feature engineering.
My top 5 new features in SQL Server 2014
SQL server 2014 is one of their measure releases. Where Microsoft has done a superb job. There are so many enhancement we have in SQL Server 2014. In my session I will show you my top 5 features.
New Analytic Functions in SQL server 2012
There are new functions introduces with the release of MS-SQL Server 2012. To perform analytic operation in T-SQL , this time Microsoft has added couple of very handy functions.