Python data analysis and visualization for self-driving cars

July 1, 2018, 3:30 p.m. - 4:00 p.m.

Artificial intelligence is revolutionizing the car, making vehicles smarter, safer, and more efficient. This breakthrough development is strongly driven by the recent rapid advances in the application of deep neural nets that learn to make decisions at accuracies that approach and surpass human expert level. The training and validation of these nets requires huge amounts of data that is collected in test-drives world-wide, which challenges classical development approaches. I will discuss how modern Big Data technologies help address these challenges. I will introduce a Python framework based on these technologies, show how we use it to process and visualize large amounts of data and illustrate its application in a deep learning use case.

Andreas Pawlik

Andreas Pawlik leads the Data Science team at NorCom, where he shares a passion for combining machines and intelligent algorithms with the goal of turning visions into rock solid data products. He discovered his interest in delivering data-driven solutions as a researcher in astrophysics, where he developed and used supercomputer simulations to investigate the formation of the universe.

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