From Philosophy to GPUs: A Data Science Journey

This chapter chronicles the speaker's transition from studying philosophy and economics to becoming a professional in machine learning and data science, sparked by a fascination with creative algorithms. It explores their contributions to NVIDIA's RAPIDS project, focusing on GPU-accelerated tools like cuML and cuDF, which significantly enhance data processing efficiency. The chapter highlights the integration of these tools into existing workflows while showcasing performance improvements and challenges in handling large datasets.