YoVDO

Optimizing Python Code Speed with Numba JIT Compiler

Offered By: The Machine Learning Engineer via YouTube

Tags

Numba Courses Machine Learning Courses Scientific Computing Courses Performance Tuning Courses Parallel Computing Courses Numerical Computing Courses

Course Description

Overview

Save Big on Coursera Plus. 7,000+ courses at $160 off. Limited Time Only!
Learn to optimize the speed of Python code using the Numba JIT (Just-in-Time) compiler in this 24-minute tutorial. Explore the implementation of jit and njit decorators to enhance code performance, and gain hands-on experience with practical examples provided in the accompanying Jupyter notebook. Discover techniques to significantly improve execution time for computationally intensive tasks, making your Python programs more efficient and responsive.

Syllabus

Optimize speed of your python code with numba JIT (Just in Time) compiler


Taught by

The Machine Learning Engineer

Related Courses

Scientific Computing
University of Washington via Coursera Biology Meets Programming: Bioinformatics for Beginners
University of California, San Diego via Coursera High Performance Scientific Computing
University of Washington via Coursera Practical Numerical Methods with Python
George Washington University via Independent Julia Scientific Programming
University of Cape Town via Coursera