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The Limitations of Big Data in Predictive Analytics

Jennifer Prendki Jennifer Prendki | Founder & CEO | Alectio

The total amount of data available to human beings currently doubles every 18-24 months, giving data scientists an unprecedented opportunity to push further than ever the boundaries of human knowledge. This is an exciting time for data professionals. Many are hopeful that these huge loads of data will enable data-greedy algorithms like deep neural networks to unlock a myriad of new possibilities for humankind.

But can big data really answer all our questions? No matter how useful and powerful, in the wrong hands, data can also easily lead to ill-informed decisions and wrong assumptions. In her talk, Jennifer will cover the reasons why better algorithms matter just as much as the amount of data available, and will describe the dangers and perils that the data scientist of the future will need to thwart using increasingly advanced mathematical knowledge, refined strategies and human rationality.

Jennifer Prendki
Jennifer Prendki
Founder & CEO | Alectio

Jennifer Prendki is the founder and CEO of Alectio. The company is the direct product of her beliefs that good models can only be built with good data, and that the brute force approach that consists in blindly using ever larger training sets is the reason why the barrier to entry into AI is so high. Prior to starting Alectio, Jennifer was the VP of Machine Learning at Figure Eight, the company that pioneered data labeling, Chief Data Scientist at Atlassian and Senior Manager of Data Science in the Search team at Walmart Labs. She has spent most of her career creating a data-driven culture wherever she went, succeeding in sometimes highly skeptical environments. She is particularly skilled at building and scaling high-performance machine learning teams and is known for enjoying a good challenge. Trained as a particle physicist (she holds a PhD in particle physics from Sorbonne University), she likes to use her analytical mind not only when building complex models but also as part of her leadership philosophy. She is pragmatic yet detail oriented. Jennifer also takes great pleasure in addressing both technical and nontechnical audiences alike at conferences and seminars and is passionate about attracting more women to careers in STEM.

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