High-performance computing with Python 3.x

Available as

Online

Summary

Learn: Use lambda expressions, generators, and iterators to speed up your code. A solid understanding of multiprocessing and multithreading in Python. Optimize performance and efficiency by leverag...

Learn: Use lambda expressions, generators, and iterators to speed up your code. A solid understanding of multiprocessing and multithreading in Python. Optimize performance and efficiency by leveraging NumPy, SciPy, and Cython for numerical computations. Load large data using Dask in a distributed setting. Leverage the power of Numba to make your Python programs run faster. Build reactive applications using Python. About: Python is a versatile programming language. Many industries are now using Python for high-performance computing projects. This course will teach you how to use Python on parallel architectures. You'll learn to use the power of NumPy, SciPy, and Cython to speed up computation. Then you will get to grips with optimizing critical parts of the kernel using various tools. You will also learn how to optimize your programmer using Numba. You'll learn how to perform large-scale computations using Dask and implement distributed applications in Python.

Show More