Key FeaturesBook DescriptionIntended to anyone interested in numerical computing and data science: students, researchers, teachers, engineers, analysts, hobbyists... Basic knowledge of Python/NumPy is recommended. Some skills in mathematics will help you understand the theory behind the computational methods.What you will learnCode better by writing highquality, readable, and welltested programs; profiling and optimizing your code, and conducting reproducible interactive computing experimentsMaster all of the new features of the IPython notebook, including the interactive HTML/JavaScript widgetsAnalyze data with Bayesian and frequentist statistics (Pandas, PyMC, and R), and learn from data with machine learning (scikitlearn)Gain valuable insights into signals, images, and sounds with SciPy, scikitimage, and OpenCVLearn how to write blazingly fast Python programs with NumPy, PyTables, ctypes, Numba, Cython, OpenMP, GPU programming (CUDA and OpenCL), parallel IPython, MPI, and many moreWho this book is for
