Explore a keynote talk from EuroPython 2016 that delves into Python's evolution as the premier language for data science. Discover how the fusion of scientific Python and conventional software practices propelled the language to the forefront of data analysis. Learn about the historical and technical aspects that contributed to Python's success in the scientific community, challenging established tools like Matlab. Gain insights into the development of scikit-learn, its technical decisions, and how it has expanded to reach a broader audience. Examine low-level technical aspects of Python's efficiency in handling large datasets, current developments in scikit-learn and joblib, and the importance of project dynamics and documentation in software success. Follow along as the speaker demonstrates practical applications by sorting EuroPython site abstracts, explores the power of numpy arrays, and discusses the interplay between numerics, control flow, and databases in data science operations. Understand the crucial role of data and computation flow in machine learning and data mining, and see how scikit-learn simplifies these complex processes for users of all skill levels. Read more