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SkillsCast

DSX (Data Science Experience) Demo

19th April 2018 in London at CodeNode

There are 3 other SkillsCasts available from AI & Deep Learning Use Cases

Data Science Experience is an IBM tool set that allows Data Scientists to create and share their Jupyter notebooks in a more collaborative and manageable way. With support for common data science environments including Python, Scala and R, as well as the majority of Machine Learning and Deep Learning frameworks. In this environment Data Scientists can work with a single source of data, exploring and manipulating it using the best of breed tools and frameworks in common usage.

Mark will showcase some of the benefits of the DSX Environment for Data Scientists, by walking the audience through a Notebook that looks at a data set of (anonymised) credit card transactions. This looks at traditional data management strategies, and also how to then make use of Machine Learning and Deep Learning frameworks to analyse this data, find patterns within that data - and ultimately build an algorithm to spot fraudulent transactions in the future.

Thanks to our sponsors

DSX (Data Science Experience) Demo

Mark Woolnough

Mark started his journey as a Support Programmer with Informix 4GL for a small, independent software vendor.  He then moved to a Consultancy role in Network Performance Management in the Telecommunications Sector working for another independent software vendor.  From there, Mark worked his way up to a Technical Account Manager before being part of a software acquisition into IBM back in 2007.

SkillsCast

Data Science Experience is an IBM tool set that allows Data Scientists to create and share their Jupyter notebooks in a more collaborative and manageable way. With support for common data science environments including Python, Scala and R, as well as the majority of Machine Learning and Deep Learning frameworks. In this environment Data Scientists can work with a single source of data, exploring and manipulating it using the best of breed tools and frameworks in common usage.

Mark will showcase some of the benefits of the DSX Environment for Data Scientists, by walking the audience through a Notebook that looks at a data set of (anonymised) credit card transactions. This looks at traditional data management strategies, and also how to then make use of Machine Learning and Deep Learning frameworks to analyse this data, find patterns within that data - and ultimately build an algorithm to spot fraudulent transactions in the future.

Thanks to our sponsors

About the Speaker

DSX (Data Science Experience) Demo

Mark Woolnough

Mark started his journey as a Support Programmer with Informix 4GL for a small, independent software vendor.  He then moved to a Consultancy role in Network Performance Management in the Telecommunications Sector working for another independent software vendor.  From there, Mark worked his way up to a Technical Account Manager before being part of a software acquisition into IBM back in 2007.