In this video presentation, our good friend Jon Krohn, Co-Founder and Chief Data Scientist at the machine learning company Nebula, explores the origins of NumPy and SciPy with their creator, Dr. Travis Oliphant. Dr. Oliphant shares his journey from personal need to global impact, the challenges overcome, and the future of these essential Python libraries in scientific computing and data science.
Video Highlights: NumPy, SciPy and the Economics of Open-Source — with Dr. Travis Oliphant
Video: Speeding Up Code with the Intel Distribution for Python
David Bolton from Slashdot shows how ‘embarrassingly parallel’ code can be sped up over 2000x (not percent) by utilizing Intel tools including the Intel Python compiler and OpenMP. “The Intel Distribution for Python* 2017 Beta program is now available. The Beta product adds new Python packages like scikit-learn, mpi4py, numba, conda, tbb (Python interfaces to Intel Threading Building Blocks) and pyDAAL (Python interfaces to Intel Data Analytics Acceleration Library). “





