Losing your Loops Fast Numerical Computing with NumPy Share: Download MP3 Similar Tracks Ned Batchelder - Facts and Myths about Python names and values - PyCon 2015 PyCon 2015 David Beazley - Python Concurrency From the Ground Up: LIVE! - PyCon 2015 PyCon 2015 Introduction to Numerical Computing with NumPy | SciPy 2019 Tutorial | Alex Chabot-Leclerc Enthought NumPy vs Pandas IBM Technology James Powell: So you want to be a Python expert? | PyData Seattle 2017 PyData Brett Slatkin - How to Be More Effective with Functions - PyCon 2015 PyCon 2015 Brandon Rhodes - Pandas From The Ground Up - PyCon 2015 PyCon 2015 Raymond Hettinger - Super considered super! - PyCon 2015 PyCon 2015 Tom Eastman - Serialization formats are not toys - PyCon 2015 PyCon 2015 But what are Hamming codes? The origin of error correction 3Blue1Brown 6. Monte Carlo Simulation MIT OpenCourseWare David Beazley - Modules and Packages: Live and Let Die! - PyCon 2015 PyCon 2015 Solving 100 Python NumPy Problems! (From easy to difficult) Keith Galli Jake VanderPlas - Performance Python: Seven Strategies for Optimizing Your Numerical Code PyCon 2018 BBC調查紀錄片:愛國者的崛起- BBC News 中文 BBC News 中文 Functional Programming in 40 Minutes • Russ Olsen • GOTO 2018 GOTO Conferences 1000x faster data manipulation: vectorizing with Pandas and Numpy PyGotham 2019 Greg Ward - How to Write Reusable Code - PyCon 2015 PyCon 2015 Jake VanderPlas - Machine Learning with Scikit-Learn (I) - PyCon 2015 PyCon 2015 Raymond Hettinger - Beyond PEP 8 -- Best practices for beautiful intelligible code - PyCon 2015 PyCon 2015