Pekka Tiusanen

Pekka Tiusanen works as a data scientist at Bilot. He holds an M.Sc. degree in economics and finished his thesis on real estate price forecasting with econometric time series models. Pekka is especially interested in machine learning and statistics.

About AI/ML Tools and Pipelines


What Do I Need and How Will It Fit? What tools for AI/ML should be adopted in my organization and how to integrate advanced analytics in data architecture? Implementations are driven by business cases with various technological requirements. There are…

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Direction of AI Technologies


Aligning AI strategy and operations with technological solutions can be challenging, but it is definitely more efficient than re-building or patching infrastructure later. The planner should have a clear overall vision of the enterprise architecture and how AI fits in…

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Making Use of Social Media Data


Relevance of Social Media Social media presence has become critically important in business life over the past decade or so. This applies to almost every business regardless of the size and industry. Especially large companies in consumer products are seeking…

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Use Cases for a Hit Rate Engine


From Abstraction to Practice Public discussion often approaches machine learning from a somewhat abstract and futuristic standpoint. In contrast, potential ML use cases are actually very practical. One of such use cases is forecasting of sales opportunity hit rates which…

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How to Build a Custom Hit Rate Engine?


About Hit Rate Forecasting Challenges in the sales process and management are common to many organizations. Improved data availability and machine learning algorithms provide means to forecast sales opportunity hit rates, which brings forth two interesting ML use cases. On…

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