Christina Voskoglou

Christina is responsible for all SlashData’s research products and heads the analyst and operations teams. With more than 18 years of experience in data mining, BI and CRM design, she leads research planning and methodology, survey design, data analysis, insights generation and research commercialisation. Christina is also behind SlashData’s outcome-based developer segmentation model and is the leading SlashData researcher in machine learning and data science.

Christina Voskoglou

Data scientists need to make sense of the big picture, rather than the big data

The web echoes with cries for help with learning data science. “How do I get started?”. “Which are the must-know algorithms?”. “Can someone point me to best resources for deep learning?”. In response, a bustling ecosystem has sprung to life around learning resources of all shapes and sizes. Are the skills to unlock the deepest secrets of deep learning what emerging data scientists truly need though? Our research has consistently shown that only a minority of data scientists are in need of highly performing predictive models, while most would benefit from learning how to decide whether to build an algorithm or not and how to make sense of it, rather than how to actually build one.

What is the best programming language for Machine Learning?

Q&A sites and data science forums are buzzing with the same questions over and over again: I’m new in data science, what language should I learn? What’s the best language for machine learning?